Behnam Vahdani
Abstract
In this research, a multi-objective mixed integer programming model is presented to design a healthcare network with risk pooling effect. Since the model parameters have also uncertainty, for closing the model to reality, using robust optimization approach, the model is also extended in a state of uncertainty. ...
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In this research, a multi-objective mixed integer programming model is presented to design a healthcare network with risk pooling effect. Since the model parameters have also uncertainty, for closing the model to reality, using robust optimization approach, the model is also extended in a state of uncertainty. Objective functions that have been used, include minimization of transportation costs, costs related to sterilization, as well as the movement of resources. We are also looking for maximizing the minimum level of service provision of healthcare centers to customers. Also, for solving the proposed model, we utilized a multi-objective fuzzy method which is developed in recent years. Moreover, several numerical examples are brought up to show the accuracy and validity of the model. The results obtained from this analysis, showed the accuracy of behavior of the model and the proposed approach in different modes. Computational results show that the robust model provides more high-quality solutions, in a way that it has far less standard deviation compared to deterministic model
mohammad reza nematollah; majid zamaheni; mohammad reza daraei; amirhossein amirkhani
Abstract
Today, the automotive industry has turned to scientific achievements for employing knowledge management One of them is the lack of attention to the work experience and skills of experienced people. The main goal of this research is to determine the framework for transforming tacit knowledge into explicit ...
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Today, the automotive industry has turned to scientific achievements for employing knowledge management One of them is the lack of attention to the work experience and skills of experienced people. The main goal of this research is to determine the framework for transforming tacit knowledge into explicit knowledge. The research methodology is applicable in terms of how to collect information from a survey type is . For this purpose, after reviewing the literature and analyzing the research gap, using the Delphi method and a survey of experts to identify possible dimensions in tacit knowledge has been discussed. The statistical population was a combination of university experts and automotive industry, and a sample of judiciary was conducted. The sample size consisted of 30 faculty members and specialists. The 4-dimensional and 4-dimensional questionnaire was extracted and 30 indicators were extracted from a 5-point Likert scale. In the first stage, all dimensions based on the literature and theoretical foundations of the research were ranked based on the obtained average and the incidence The panel members' opinion was reached, and in the second phase of the Delphi agreement, the same agreement as the first stage was created among panel members, and the survey was stopped according to theoretical saturation. The research findings show that, in terms of experts in four organizational dimensions, planning and project startup, conquer And modeling of tacit knowledge and explicit knowledge of documentary knowledge can be used as a framework for the transformation of tacit knowledge Explicit knowledge is named.
Hêriş Golpîra; Erfan Babaee Tirkolaee; Mohammad Taghi Taghavifard; Fayegh Zaheri
Abstract
Although the construction industry, especially because of its relationship with other economic sectors, is one of the most important sectors that plays a key role in a country's economic growth, the construction supply chain has been considered less attention. Therefore, construction supply chain network ...
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Although the construction industry, especially because of its relationship with other economic sectors, is one of the most important sectors that plays a key role in a country's economic growth, the construction supply chain has been considered less attention. Therefore, construction supply chain network design is of great importance for not only the companies but also governments. Thus, presenting an original mixed integer linear programming model, this paper introduces an optimal framework for a multi-project multi-resource multi-supplier construction supply chain network design for large construction companies with a decentralized procurement strategy. The main objective is to design a reliable supply chain model based on the quality of projects under the certain predefined budget, considering the entire supply chain as a single entity. Using a bi-objective approach to formulate the chain and the Lp-metric approach to solve the problem, make it possible to obtain a single-objective structural framework to reliability-quality trade-off consideration. To solve the problem in small and medium scales, GAMS software is employed, and a hybrid algorithm based on Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm is developed to solve the large-scaled problem. The results show the capability of the model to attain optimal size of the chain as well as the quality-reliability trade-off considering a pre-specified budget. And, to the best of authors knowledge this is the first to obtain such a structured integrated framework in the construction supply chain.
Mohammad Mohammadi; Kamran Forghani
Abstract
The cell formation problem and the group layout problem, both are two important problems in designing a cellular manufacturing system. The cell formation problem is consist of grouping parts into part families and machines into production cells. In addition, the group layout problem is to find the arrangement ...
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The cell formation problem and the group layout problem, both are two important problems in designing a cellular manufacturing system. The cell formation problem is consist of grouping parts into part families and machines into production cells. In addition, the group layout problem is to find the arrangement of machines within the cells as well as the layout of cells.In this paper, an integrated approach is presented to solve the cell formation, group layout and routing problems. By Considering the dimension of machines, the width of the aisles, and the maximum permissible length of the plant site, a new framework, called spiral layout, is suggested for the layout of cellular manufacturing systems. To extend the applicability of the problem, parameters such as part demands, operation sequences, processing times and machine capacities are considered in the problem formulation. The problem is formulated as a bi-objective integer programming model, in which the first objective is to minimize the total material handling cost and the second one is to maximize the total similarity between machines. As the problem is NP-hard, three metaheuristic algorithms, based on Genetic Algorithm and Simulated Annealing are proposed to solve it. To enhance the performance of the algorithms, a Dynamic Programming algorithm is embedded within them. The performance of the algorithms is evaluated by solving numerical examples from the related literature. Finally, a comparison is carried out between the proposed spiral layout and the linear multi-row layout which has recently presented in the literature
supply chain management
Abolfazl Kazai; amir mohammad khani; soraya birami
Abstract
As an important dimension of company performance, the impact of supply chain quality management (SCQM) on innovation performance has not been studied in internal studies. In addition, internal research into the capabilities of SCQM, a key driver for SCQM, has been very limited. To fill this research ...
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As an important dimension of company performance, the impact of supply chain quality management (SCQM) on innovation performance has not been studied in internal studies. In addition, internal research into the capabilities of SCQM, a key driver for SCQM, has been very limited. To fill this research gap, this paper examines how SCQM capabilities and SCQM performance can influence firm innovation and operational performance, and how they interact with each other. For this purpose, the information of managers and experts active in the food industry in Golestan province was collected and analyzed through a questionnaire. Research findings show that SCQM practices have a positive effect on SCQM capabilities. Another result is that SCQM methods do not have a positive effect on the operational performance of food industries in Golestan province. This finding is significantly different from some previous studies. We also found that SCQM capabilities do not have a positive effect on innovation performance.
Nastaran Bakhshizadeh; Parham Azimi
Abstract
In nowadays market, the increased level of competitiveness and uneven fall of the product/service demands are pushing enterprises to make key efforts for optimization of their process management. It involves collaboration in multiple dimensions including information sharing, capacity planning, and reliability ...
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In nowadays market, the increased level of competitiveness and uneven fall of the product/service demands are pushing enterprises to make key efforts for optimization of their process management. It involves collaboration in multiple dimensions including information sharing, capacity planning, and reliability among players. One of the most important dimensions of the supply chain network is to determine its optimal operating conditions incurring minimum total costs. However, this is even a tough job due to the complexities inherit the dynamic interaction among multiple facilities and locations. In order to resolve these complexities and to identify the optimal operating conditions, we have proposed a hybrid approach via integrating the simulation technique, Taguchi method, robust multiple non-linear regression analysis and the Harmony Search algorithm, which is the main contribution of the research. In the first experiment, design concepts are used to define a number of scenarios for the supply chain. Then each of these scenarios is implemented in a simulated environment. The results of the simulation used to estimate the relationship between the chain and chain cost factors. This relationship can be used to optimize the supply chain which minimizes the system costs. This research provides a framework to understand the intricacies of the dynamics and interdependency among the various factors involved in the supply chain. It provides guidelines to the manufacturers for the selection of appropriate plant capacity and proposes a justified strategy for delayed differentiation.
S.R. Salami; M. Goodarzi
Volume 1, Issue 3 , January 2003, , Pages 73-95
Abstract
The main objective of this article is to study the role of intellectual property Rights (IPRs) in the technological development of development countries in general and Iran in particular. Firstly some of the main relevant literature of the role of IPRs in technological development has been surveyed. ...
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The main objective of this article is to study the role of intellectual property Rights (IPRs) in the technological development of development countries in general and Iran in particular. Firstly some of the main relevant literature of the role of IPRs in technological development has been surveyed. The performance of the IPRs system of the country and its interaction with national innovation system with some selected countries including japan S Korea and China has been discussed. Some internal and external experts in the area of IPRs have been interviewed. Finally some suggestions and policy implication regarding the improvement and promotion of IPRs system in Iran have been presented.
S. Ketabi; A. Hagh Shenas; A. Hadadian
Volume 4, Issue 12 , March 2006, , Pages 73-96
perfomance management
Leila Parhizkar Miyandehi; Alireza Amirteimoori; Sohrab Kordrostami; Mansour Soufi
Abstract
Estimating the revenue efficiency of entities being evaluated is crucial as it provides valuable information about organizations, assuming that the output prices are known. This research introduces a new definition of optimal scale size (OSS) based on maximizing the average revenue efficiency (ARE). ...
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Estimating the revenue efficiency of entities being evaluated is crucial as it provides valuable information about organizations, assuming that the output prices are known. This research introduces a new definition of optimal scale size (OSS) based on maximizing the average revenue efficiency (ARE). Additionally, the ARE is defined for both convex and non-convex sets, independent of returns to scale and the assumption that the vector of input-output prices of units is uniform. Moreover, to address the presence of uncertain data in real-world applications, the introduced ARE model is extended to evaluate systems with random inputs and outputs, along with approaches for its calculation. Finally, the proposed method is applied in an experimental example, calculating the ARE for a dataset of postal areas in Iran.IntroductionThe concept of optimal scale size has been extensively studied in the field of data envelopment analysis. Cesaroni and Giovannola's research on non-convex FDH technology reveals that the optimal scale size is a point in the production possibility set that minimizes average cost efficiency. Average cost efficiency, a new measure combining scale and allocation efficiencies, provides a more accurate performance assessment compared to cost and scale efficiencies. When evaluating units with known output prices instead of input prices, assessing revenue efficiency can offer more valuable insights. This paper extends the research on cost evaluation to revenue evaluation. It introduces the concepts of average revenue efficiency and optimal scale size based on revenue maximization. The optimal scale size based on revenue maximization is defined as the point in the production possibility set that maximizes the average radial income for the unit under investigation. Average revenue efficiency serves as an evaluation measure of unit revenue, surpassing revenue and scale efficiencies in accuracy. The paper examines methods for calculating average revenue efficiency in both convex and non-convex technologies. It demonstrates that the average revenue efficiency model in convex technology with variable returns to scale is equivalent to the revenue model with constant returns to scale. Furthermore, the relationship between optimal scale size points based on revenue maximization and the most productive scale size is determined. Next, the paper presents the average revenue efficiency model for stochastic sets with the presence of stochastic data. An experimental example is used to calculate the average revenue efficiency and obtain the optimal scale size for a set of postal areas in Iran.Materials and MethodsThe study builds upon Cesaroni and Giovannola's method for calculating average cost efficiency and optimal scale size to develop models for average revenue efficiency and optimal scale size based on revenue. It also utilizes chance-constrained probabilistic models with a deterministic objective function in DEA literature to present average revenue efficiency for stochastic sets. The model is transformed from stochastic to deterministic and then converted into a linear model using the error structure method.Discussion and ResultsThis paper introduces average revenue efficiency and optimal revenue scale size, demonstrating the equivalence between the average revenue efficiency models in convex technology with variable returns to scale and those with constant returns to scale. It also presents the average revenue efficiency model for stochastic sets, enabling the calculation of average revenue efficiency and optimal revenue scale size for units with random inputs and outputs.ConclusionIn many real-world scenarios, particularly when output prices are known, evaluating revenue efficiency holds greater significance than cost efficiency. This study develops the concepts of average cost efficiency and optimal scale size for revenue evaluation, expanding upon the existing literature on data envelopment analysis. The paper demonstrates how average revenue efficiency can be calculated as a valuable and accurate measure of efficiency in convex and non-convex technologies, without making assumptions about returns to scale. By assuming the randomness of input and output variables and employing chance-constrained models, a quadratic deterministic model is presented to calculate average revenue efficiency. It is then transformed into a linear model assuming uncorrelated variables, enabling the determination of average revenue efficiency and optimal scale size based on revenue maximization for random units. The proposed models are applied to a real-world sample, evaluating the average revenue efficiency of twelve postal units. The results highlight the models' ability to provide a more accurate evaluation of revenue efficiency and identify the best revenue scale size as the reference for inefficient units.
Mahdi Nasrollahi
Abstract
Due to fierce competition and customer demand, manufacturers have started selling products with different warranty policies and pro-rata warranty is one of the most widely used warranty policy. In this paper we propose a warranty model for pro-rata, fixed period warranty policy with risk averse manufacturer ...
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Due to fierce competition and customer demand, manufacturers have started selling products with different warranty policies and pro-rata warranty is one of the most widely used warranty policy. In this paper we propose a warranty model for pro-rata, fixed period warranty policy with risk averse manufacturer that determines optimal warranty price under inflationary condition.This model has been proposed for products with time dependent failure intensity with Non homogeneous Poisson’s process for failure intensity function, and concave utility function. Using the exponential utility function, the decision model is developed to maximize the manufacturer’s certainty profit equivalent. Risk preference model is developed to find the optimal warranty price through the use of the manufacturer’s utility function for profit. Finally, the sensitivity of the warranty price models is analyzed using numerical examples with respect to such factors as (1) the manufacturer's risk preferences, (2) product failure rate parameters, (3) warranty period length, and (4) inflation and discount rate
maedeh mosayeb motlagh; Parham Azimi; maghsoud Amiri
Abstract
This paper investigates unreliable multi-product assembly lines with mixed (serial-parallel) layout model in which machines failures and repairing probabilities are considered. The aim of this study is to develop a multi-objective mathematical model consisting the maximization of the throughput rate ...
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This paper investigates unreliable multi-product assembly lines with mixed (serial-parallel) layout model in which machines failures and repairing probabilities are considered. The aim of this study is to develop a multi-objective mathematical model consisting the maximization of the throughput rate of the system and the minimization of the total cost of reducing mean processing times and the total buffer capacities with respect to the optimal values of the mean processing time of each product in each workstation and the buffer capacity between workstations. For this purpose, in order to configure the structure of the mathematical model, Simulation, Design of Experiments and Response Surface Methodology are used and to solve it, the meta-heuristic algorithms including Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Ranked Genetic Algorithm (NRGA) are implemented. The validity of the multi-objective mathematical model and the application of the proposed methodology for solving the model is examined on a case study. Finally, the performance of the algorithms used in this study is evaluated. The results show that the proposed multi-objective mathematical model is valid for optimizing unreliable production lines and has the ability to achieve optimal (near optimal) solutions in other similar problems with larger scale and more complexity.IntroductionA production line consists of a sequence of workstations, in each of which parts are processed by machines. In this setup, each workstation includes a number of similar or dissimilar parallel machines, and a buffer is placed between any two consecutive workstations. In production lines, the buffer capacity and processing time of machinery have a significant impact on the system's performance. The presence of buffers helps the system to maintain production despite possible conditions or accidents, such as machinery failure or changes in processing time. Previous research has investigated production lines without any possibility of machinery failure, referred to as "safe production lines." However, in real production lines, machinery failure is inevitable. Therefore, several studies have focused on "uncertain production lines,"assuming the existence of a probability of failure in a deterministic or exponential distribution. This research examines uncertain production lines with a combined layout, resulting from the combination of parallel deployment of machines within each workstation, if necessary, and serial deployment of workstations. The objective of this research is to determine the optimal values (or values close to optimal) of the average processing time of each product in each workstation, as well as the volume of buffers, as decision variables. The approach aims to maximize the system's output while minimizing the costs associated with reducing the processing time of workstations and minimizing the total volume of buffers between stations. Moreover, simulation can be applied without interrupting the production line or consuming significant resources. In this research, due to the high cost and time involved, implementing the proposed changes on the system is not cost-effective for investigating the changes in the production system's output rate. Therefore, the simulation technique has been utilized to optimize the production line.Research methodThe present study aims to develop a multi-objective mathematical model, based on simulation, to optimize multi-product production lines. In the first step, the structure of the multi-objective mathematical model is defined, along with the basic assumptions. To adopt a realistic approach in the model structure, the simulation technique has been employed to address the first objective function, which is maximizing the output rate of the production line. To achieve this, the desired production system is simulated. The design of experiments is used to generate scenarios for implementation in the simulated model, and the response surface methodology is utilized to analyze the relationship between the input variables (such as the average processing time of each product type in each workstation and the buffer volume between stations) and the response variable (production rate).ResultsTo implement the proposed methodology based on the designed multi-objective programming model, a case study of a three-product production line with 9 workstations and 8 buffers was conducted. Subsequently, to compare the performance of the optimization algorithms, five indicators were used: distance from the ideal solution, maximum dispersion, access rate, spacing, and time. For this purpose, 30 random problems, similar to the mathematical model of the case study, were generated and solved. Based on the results obtained, both algorithms exhibited similar performance in all indices, except for the maximum dispersion index.ConclusionsIn this article, the structure of a multi-objective mathematical model was sought in uncertain multi-product production lines with the combined arrangement of machines in series-parallel (parallel installation of machines in workstations if needed and installation of workstations in series). The objective was to determine the optimal values of the average processing time of each type of product in each workstation and the buffer volume of each station, with the goals of maximizing the production rate, minimizing the costs resulting from reducing the processing time, and the total volume of inter-station buffers simultaneously. To investigate the changes in the output rate of the production system, due to the high cost and time, it was deemed not cost-effective to implement the proposed changes on the system. Therefore, the combination of simulation techniques, design of experiments, and response surface methodology was used to fit the relevant metamodel. In the proposed approach of this research, taking a realistic view of production line modeling, the probability of machinery failure, as well as the possibility of repairability and return to the system, were considered in the form of statistical distribution functions. Additionally, all time parameters, including the arrival time between the parts, the start-up time of all the machines, the processing time, the time between two failures, and the repair time of the machines, were non-deterministic and subject to statistical distributions. Finally, to solve the structured mathematical model, two meta-heuristic algorithms (NSGA-II) and (NRGA) were considered.
project management
ali mohaghar; Fatemeh Saghafi; Ebrahim Teimoury; Jalil Heidary Dahooie; Abdolkarim sabaee
Abstract
The application of supply chain management within the construction industry presents significant challenges due to the transient nature of construction projects, high levels of customization, low repeatability of activities, absence of a production line, and interdependent relationships among activities. ...
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The application of supply chain management within the construction industry presents significant challenges due to the transient nature of construction projects, high levels of customization, low repeatability of activities, absence of a production line, and interdependent relationships among activities. Construction supply chains are intricate systems, where the final performance results from numerous decisions made across multiple independent companies. Interactions among supply chain stakeholders and the unique characteristics of each project create complex phenomena with multiple interconnected elements and variables. The Viable System Model (VSM), rooted in organizational cybernetics, provides a structured approach to addressing complex and unstructured problems. This structured approach allows analysts to gain in-depth insights into the functional issues of the existing system and understand how to modify the system design to adapt to internal and external disruptions.MethodologyDespite the extensive capabilities of the Viable System Model as a diagnostic tool for assessing organizational structure and achieving viability, a systematic and distinct methodology for its application is lacking. Researchers in VSM often do not employ a specific methodology for systems analysis. In this study, we propose a methodology for applying the VSM as a diagnostic tool for organizations, derived from a review of theoretical foundations and practical requirements of VSM. Building on Jackson's methodology outlined in his book "System Thinking, Creative Holism for Managers," we have developed a methodology by integrating Jackson's approach with case study research. This methodology includes stages such as designing a diagnostic framework, selecting case studies, identifying systems, conducting system diagnosis, and validating the model. We applied this methodology to diagnose the supply chain of an Iranian petrochemical construction project, resulting in the development of a viable system model. The validity of the research methodology and findings was confirmed through expert participation and the application of multiple qualitative criteria.ResultsFollowing the selection of a case study and the identification of systems, we investigated the existence and function of five subsystems and communication channels within the focal system using a case study approach to gather information and develop the viable system model. Data was collected through semi-structured interviews conducted at various managerial and technical levels within a prominent project-oriented company in Iran's petrochemical industry. These interviews lasted between 45 and 60 minutes each. Data collection methods also included observation and document examination. The research involved a semi-structured interview with 18 individuals to explore complications within each of the five systems. Subsequently, the collected data was adapted to the model's requirements, and findings were extracted through intra-case analysis and coding. This process led to model development and the identification of weaknesses within the construction supply chain from the perspective of the five systems and communication channels, with a focus on achieving viability.ConclusionsThe developed model highlights weaknesses and bottlenecks within the focal system, shedding light on the most significant issues. A critical issue identified in the case study is the evident lack of coherence within System 4 and System 5. The results reveal that the incoherence of System 5, divided between parts of the company at level 0 and the parent company at a higher recursion level outside the focal system, results in defects within the communication channels related to this system, including C14 (Connection of System 4 with System 5), C9 (Algedonic channel), and C16 (Connection of System 5 with the homeostatic loop of Systems 3 and 4). Additionally, System 4, which is jointly managed by a segment of the company and the project management consultant, leads to disruptions in channels related to this system, particularly C13 (Homeostatic loop between Systems 3 and 4), C14 (Communication between System 4 and System 5), and C15 (Homeostat of System 4 with the future environment). Concerning common errors, the dominant error is E5, attributed to the lack of coherence between Systems 4 and 5 and the weak performance of System 2. This error largely stems from inconsistencies between the two operational units responsible for the engineering phase and the construction and installation phase. To achieve viability within the focal system, several measures should be taken, including the establishment of centralized Systems 4 and 5 within the company and strengthening communication channels with incomplete or insufficient capacity. These channels include the connection between System 4 and System 5 (C14), the Algedonic channel (C9), the connection of System 5 with the homeostatic loop of Systems 3 and 4 (C16), the homeostatic loop of System 3 and System 4 (C13), and the homeostat of System 4 with the future environment (C15). A crucial homeostatic link involves the communication and interaction between System 3 and System 4 (C13) to establish dynamic communication between the current project environment and its future. However, the interaction between these two systems is currently conflicting and misaligned due to the lack of coherence within System 4 and differences in functionality between System 3's perspective on the current state and System 4's perspective on the future state. Balancing the emphasis on System 4 and the future with the daily operations of the supply chain's operational units within System 1 is essential to avoid supply chain disruptions or inefficiencies. The lack of coherence within System 4 also affects the performance of other systems, particularly System 5, as well as the stability of System 4 in relation to the future environment. Inadequate information about the future environment can hinder informed decision-making within the system. By addressing these points within the model, the construction project's supply chain can move toward viability and better adapt to changes in the project environment. This research represents one of the limited studies in the implementation of VSM within the construction project environment.
Amir Khorrami; Mohammad Taghi Taghavifard; Seyed Mohammad Ali Khatami Firouzabadi
Abstract
Credit risk assessment is one of the key issues for banks and financial institutions and various models have been developed for this. This study uses Case Based reasoning (CBR) Model and considers a database of bank credit customers to assess the credit risk of bank applicants. For this, 9 criteria were ...
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Credit risk assessment is one of the key issues for banks and financial institutions and various models have been developed for this. This study uses Case Based reasoning (CBR) Model and considers a database of bank credit customers to assess the credit risk of bank applicants. For this, 9 criteria were selected based on the experts' opinion and were weighted using the Fuzzy Analytical Hierarchy Process (FAHP). Return check, housing situation and income level are the most important criteria for credit risk assessment of the bank applicants. Then, using the TOPSIS Technique, we could evaluates the similarity of the new item with actual past cases or evaluate the new applicant with the ideal option, and uses a case-based reasoning model to predict the likelihood of default or non-default applicants. Survey research was applied for this study and the research community was the records of previous bank applicants between 1390-94 years. This research is an applied and descriptive and descriptive study. The results show that the accuracy of the CBR model is higher than other validation and ranking methods of bank customers. The use of the CBR model in order to authenticate customers has obtained results far better than the performance of the credit sector experts, which led to the judgment of default or non-default of customers, indicating the high performance of the model used in comparison to the model used by bank and validation experts. CBR leads to the design an expert, specialized and intelligent system which addition to storing data in a database, stores models and templates for use.
safety,risk and reliability
Seyedeh Sara Khorashadizadeh; Jalal Haghighat Monfared; Mohammadali Afshar Kazemi; Shahram Yazdani
Abstract
In this study, a comprehensive classification for supply chain risks in the pharmaceutical industry is presented using the Bailey’s classical strategy method and the four-stage Collier method. Initially, through the examination of texts related to the main hazard groups, supply chain elements, ...
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In this study, a comprehensive classification for supply chain risks in the pharmaceutical industry is presented using the Bailey’s classical strategy method and the four-stage Collier method. Initially, through the examination of texts related to the main hazard groups, supply chain elements, considering resources and functions, and categorizing upstream supply chain organizations, primary industry, and downstream supply chain organizations within the industrial and market environment, infrastructural environment, and external macro environment were modeled. In the next stage, criteria related to the security and safety of the supply chain were identified. In the final stage, a two-dimensional matrix classification for the identification of supply chain risk factors was proposed through the cross-tabulation of supply chain elements with security and safety criteria. Based on this classification and utilizing the exemplification method through a synthetic framework, a detailed list of risk factors was compiled. The aim of this study is to propose a comprehensive risk classification for pharmaceutical industries.MethodBailey’s classical strategy method has been used to develop a comprehensive classification of supply chain risks in pharmaceutical industries. In order to review the existing knowledge about supply chain risk groups, a systematic review of literature was performed. In the first stage, to find articles related to supply chain risks in the pharmaceutical industry, different combinations of related keywords have been used to search for articles in relevant databases. The selected articles were examined in three stages: extracting and classifying the main risk groups of the supply chain (the first dimension of the conceptual framework of classification), extracting and classifying criteria for a low-risk supply chain (the second dimension of the conceptual framework of classification), and applying the two-dimensional framework of classification to identify and classify risk factors of the supply chain.ResultsA total of 77 articles were selected for review. Based on the analysis of these articles, 83 risk groups were identified. These risk groups were arranged into a model including upstream supply organizations, the main industry, and downstream supply organizations, considering the relationships between supply chain’s resources, functions, and outcomes in the industry and market environment, infrastructural environment, and external macro environment. In the next step, 30 criteria for a safe and secure supply chain were identified. These criteria are divided into two general categories: criteria for the security of the internal supply chain environment (criteria of resistant supply chain resources and criteria of resilient supply chain functions) and criteria for the safety of the external supply chain environment (criteria of safety of market and industry, criteria of safety of infrastructural environment, and criteria of safety of external macro environment). In the last stage, through cross-tabulation of resource groups with resource resistance criteria, function groups with function resilience criteria, and peripheral environment elements with peripheral environment safety criteria, a model for identifying risk factors in the industrial environment was proposed. Based on this model, 372 risk factors of the supply chain of the pharmaceutical industry were identified.ConclusionIn this study, a new classification for supply chain risks of the pharmaceutical industry has been presented. The proposed classification is highly comprehensive, and the number of risk groups counted in this study is more than all the studies that have been done in this field so far. Most existing risk taxonomies are incomplete and do not follow a specific theoretical model. The classification of risk groups identified in this study has been done based on a model that considers the relationship between assets, functions, and outcomes of the supply chain. The risk groups identified in this study cover from the upstream of the supply chain to the main industry and the downstream of the supply chain. Many risk taxonomies focus on the pharmaceutical industry and do not cover the entire supply chain from raw material production to customers. In this study, cross-tabulation of resource groups with resource resistance criteria, function groups with function resilience criteria, and peripheral environment elements with peripheral safety criteria create an ideal model for identifying risk factors in the industrial environment. The classification proposed in this study can be used to evaluate the resistance and resilience of the supply chain. This model can also provide a suitable basis for identifying and evaluating risks in the supply chain environment. In addition, results of this study provide a very practical guide for choosing supply chain risk management strategies.
Abstract
Overally location problem could be classified as desirable facility location and undesirable facility location. In the undesirable facility location problem contrary to desirable location, facilities are located far from service receiver facilities as much as possible. The problem of locating such facilities ...
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Overally location problem could be classified as desirable facility location and undesirable facility location. In the undesirable facility location problem contrary to desirable location, facilities are located far from service receiver facilities as much as possible. The problem of locating such facilities is discussed in this paper. This research is focused on the “not in my backyard” (NIMBY) which refers to the social phenomena in which residents are opposed to locate undesirable facilities around their houses. Examples of such facilities include electric transmission lines and recycling centers. Due to the opposition typically encountered in constructing an undesirable facility, the facility planner should understand the nature of the NIMBY phenomena and consider it as a key factor in the determining facility location. A integer linear model of this problem and a Lagrange relaxation method are proposed in this research. This method relaxes up the hard constraints and adds the constraints to the objective function with a Lagrangian multiplier. To show that the Lagrangian relaxation method is computationally powerful exact solution algorithm and is capable to solve the medium-size problems, the performance of the proposed algorithm is examined by applying it to several test problems.
Mohammad Nikzamir; vahid baradaran; Yunes Panahi
Abstract
Health care solid wastes include all types of waste that are produced as a result ofmedical and therapeutic activities in hospitals and health centers. About 15% to20% of these waste materials are infectious waste, which falls within the categoryof hazardous materials. Infectious waste is the one that ...
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Health care solid wastes include all types of waste that are produced as a result ofmedical and therapeutic activities in hospitals and health centers. About 15% to20% of these waste materials are infectious waste, which falls within the categoryof hazardous materials. Infectious waste is the one that must be treated beforedisposal or recycling. Hence, this paper seeks to develop a bi-objective mixedinteger programming model for the infectious waste management. In the proposedmodel, in addition to minimizing the chain costs, the reduction of risks for thepopulation exposed to the spread of contamination resulting from infectious wasteis also considered. For this purpose, a multi-echelon chain is proposed by takinginto account the green location-routing problem, which involves the location ofrecycling, disposal, and treatment centers through various treatment technologiesand routing of vehicles between treatment levels and the hospital. The routingproblem has been considered to be multi-depot wherein the criterion of reducingthe cost of fuel consumption of heterogeneous cars is used for green routing.Finally, a hybrid meta-heuristic algorithm based on ICA and GA is developedand, following its validation, its function in solving large-scale problems has beeninvestigated. Results show that the proposed algorithm is effective and efficient.
safety,risk and reliability
Amir Yousefli; reza Norouzi; Amir Hosein Hamzeiyan
Abstract
Reliability Redundancy Allocation (RRA) is one of the most important problems facing the managers to improve the systems performance. In the most RRA models, presented in the literature components’ reliability used to be assumed as an exact value in (0,1) interval, while various factors might affect ...
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Reliability Redundancy Allocation (RRA) is one of the most important problems facing the managers to improve the systems performance. In the most RRA models, presented in the literature components’ reliability used to be assumed as an exact value in (0,1) interval, while various factors might affect components’ reliability and change it over time. Therefore, components reliability values should be considered as uncertain parameters. In this paper, by developing a discrete - continuous inference system, an optimization - oriented decision support system is proposed considering the components’ reliability as stochastic variables. Proposed DSS uses stochastic if - then rules to infer optimum or near optimum values for the decision variables as well as the objective function. Finally, In order to evaluate the efficiency of the proposed system, several examples are provided. Comparison of the inferred results with the optimal values shows the very good performance of the developed stochastic decision support system.
project management
Yahya Dorfeshan; Seyed Meysam Mousavi; Behnam Vahdani
Abstract
Critical path method is one of the most widely used approaches in planning and project control. Time is considered a determinative criterion for the critical path. But it seems necessary to regard other criteria in addition to time. Besides time criterion, effective criteria such as quality, cost, risk ...
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Critical path method is one of the most widely used approaches in planning and project control. Time is considered a determinative criterion for the critical path. But it seems necessary to regard other criteria in addition to time. Besides time criterion, effective criteria such as quality, cost, risk and safety are considered in this paper. Then, the developed problem is solved as a multi-attribute decision making problem by a new extension of MULTIMOORA method. Moreover, type-2 fuzzy sets are utilized for considering uncertainties. Type-2 fuzzy sets are more flexible and capable than type-1 fuzzy sets in reflecting uncertainties. Eventually, SWARA method is developed for determining the weights of efficient criteria such as time, cost, quality, risk and safety under type-2 fuzzy environment. Finally, an applied example has been solved to illustrate the calculations and the ability of the proposed approach. Based on the example, it is clear that the longest path in terms of time criterion is not a critical path, and other influential criteria are involved in determining the critical path. IntroductionToday, in the competitive business environment, project management, planning, scheduling, and project control hold significant importance. One of the widely used and common methods in the field of project planning and control is undoubtedly the Critical Path Method (CPM). In the Critical Path Method, activity durations are predetermined. However, in the real world, many projects and activities are executed for the first time and have considerable uncertainties. Therefore, obtaining an accurate estimate of the time and resources required for activities is challenging. However, considering a single criterion, such as time, will not yield fruitful results, and other influential parameters such as risk should also be taken into account. For example, a path that carries a high level of risk may not be the critical path at present, but it may become critical in the future due to the high risk involved. For this reason, this research explores other influential criteria besides time and considers them in determining the critical path.Materials and MethodsIn this study, the problem under investigation is the determination of the critical path while considering other influential criteria in addition to the time criterion. To achieve this, multiple criteria decision-making methods are used to consider criteria such as time, cost, quality, risk, and safety in determining the critical path. Furthermore, to account for the uncertainties of the real world and incorporate expert opinions, type-2 fuzzy sets are utilized. It should be noted that the MULTIMOORA method is employed for ranking the critical paths, while the SWARA method is used to determine the weights of the influential criteria in determining the critical path. Both methods have been extended and developed in a type-2 fuzzy environment.Discussion and Results Initially, the proposed method is solved considering only the time criterion. As observed, the critical path has changed, indicating the importance of other criteria in determining the critical path. Then, the proposed method is solved considering pairwise combinations of the criteria, where the time criterion is treated as a fixed criterion due to its high importance. In fact, the problem is solved considering time and cost, time and risk, time and quality, and time and risk. By increasing or decreasing each criterion, the critical path changes, demonstrating the significance of all criteria in determining the project's critical path. To determine the critical path, it is necessary to consider all criteria together. These variations in the criteria and the resulting change in the critical path clearly indicate the importance and influence of other criteria in determining the critical path.ConclusionIn this article, an extension of the MULTIMOORA multi-criteria decision-making method is presented in the reference section. Additionally, Type-2 fuzzy numbers, which offer more flexibility and better representation of uncertainties compared to Type-1 fuzzy numbers, are utilized. The MULTIMOORA multi-criteria decision-making method is developed to incorporate these Type-2 fuzzy numbers. The opinions of three experts are used numerically for the time and cost criteria and linguistically as linguistic variables for the quality, risk, and safety criteria. Ultimately, the weights of the influential criteria of time, cost, risk, quality, and safety are determined using the developed SWARA method under Type-2 fuzzy environment. Finally, the most critical path is determined by considering not only the time criterion but also the influential criteria of cost, quality, risk, and safety. Based on the conducted research, a set of criteria including time, cost, quality, risk, and safety are used in this article, and additional criteria can also be added to this set.
Ahmad Ahmadi; Abolfazl Kazai; Mohammad Naghizadeh; Maghsood Amiri
Abstract
Following Chesbrough's statements of open innovation as a spectrum rather than a dichotomy, many studies have been conducted to reflect the dynamics in its implementation in the form of typologies, modes, themes, and mechanisms. These studies, with considering only some aspects of the innovation process, ...
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Following Chesbrough's statements of open innovation as a spectrum rather than a dichotomy, many studies have been conducted to reflect the dynamics in its implementation in the form of typologies, modes, themes, and mechanisms. These studies, with considering only some aspects of the innovation process, have tried to develop a method for classifying and providing a model for adoption of open innovation. After reviewing the literature and interviewing with experts, the components and factors in each implementation step were obtained. Finally, to analyze and plot the interrelationships between the various components of the open innovation model DMATELE technique was used. Consequently, the open innovation model was determined in the study company. This model is the result of a chain of decisions in relation to each component of OI model within the phases of the innovation process. The decision chains include: selecting the “pre-print” domain as content of the model, choosing the direction of “market driven –invitational” for actors, and choosing mechanisms for increasing “absorptive capacity”, “transformative and connective capacity”, and “desorptive capacity.”
Abstract
One of the most important problems of logistic networks is designing and analyzing of the distribution network. The design of distribution systems raises hard combinatorial optimization problems. In recent years, two main problems in the design of distribution networks that are location of distribution ...
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One of the most important problems of logistic networks is designing and analyzing of the distribution network. The design of distribution systems raises hard combinatorial optimization problems. In recent years, two main problems in the design of distribution networks that are location of distribution centres and routing of distributors are considered together and created the location-routing problem. The location-routing problem (LRP), integrates the two kinds of decisions. The classical LRP, consists in opening a subset of depots, assigning customers to them and determining vehicle routes, to minimize total cost of the problem. In this paper, a dynamic capacitated location-routing problem is considered that there are a number of potential depot locations and customers with specific demand and locations, and some vehicles with a certain capacity. Decisions concerning facility locations are permitted to be made only in the first time period of the planning horizon but, the routing decisions may be changed in each time period. In this study, customer demands depend on the products offering prices. The corresponding model and presented results related to the implementation of the model by different solution methods have been analysed by different methods. A hybrid heuristic algorithm based on particle swarm optimization is proposed to solve the problem. To evaluate the performance of the proposed algorithm, the proposed algorithm results are compared with exact algorithm optimal value and lower bounds. The comparison between hybrid proposed algorithm and exact solutions are performed and computational experiments show the effectiveness of the proposed algorithm.
Maryeh Nematizadeh; Alireza Amirteimoori; Sohrab Kordrostami; Leila Khoshandam
Abstract
The electricity industry plays a pivotal role in a country's economic growth and development. Therefore, it is imperative to assess its performance and identify the strengths and weaknesses of its different sectors, such as production, transmission, and distribution, to enhance economic growth in diverse ...
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The electricity industry plays a pivotal role in a country's economic growth and development. Therefore, it is imperative to assess its performance and identify the strengths and weaknesses of its different sectors, such as production, transmission, and distribution, to enhance economic growth in diverse areas. Given the significance of the transmission sector, this research focuses on analyzing and evaluating the performance of 16 regional electricity companies in Iran from 1390 to 1398, with the aim of comprehending the impact of contextual variables on efficiency. To achieve this, the study will utilize two techniques - Data Envelopment Analysis (DEA) and Ordinary Least Squares (OLS) - to determine the efficiency score and estimate the effect of contextual variables on efficiency, respectively. In the first stage, the DEA technique is employed to calculate the technical efficiency of each company, considering their specific inputs and outputs. In the second stage, the logarithm of the efficiency scores obtained is regressed on contextual variables to establish their effect on efficiency. The residual derived from the regression is referred to as managerial ability. Finally, the companies are ranked based on their modified efficiency after removing the impact of contextual variables.
Introduction
The electricity industry comprises three key sectors: production, transmission, and distribution. It stands as one of the most crucial economic infrastructures in the country, exerting significant influence on industrial, agricultural, service, and other sectors. Undoubtedly, the growth of the electricity industry drives the nation's economic development and progress, contributing to the prosperity and comfort of its citizens (Tavassoli et al., 2020). Consequently, analyzing and examining the growth trajectory of each sector across different years becomes pivotal in mitigating adverse effects and fostering progress within this domain.
In recent years, numerous researchers have conducted studies in this field. Some have independently evaluated each production, transmission, and distribution sector, while others have adopted a comprehensive approach by considering the integrated three-stage network structure. The research background highlights that the transmission sector has received less attention from researchers than other sectors. This is noteworthy because, following electricity production, the transmission process and energy accessibility to consumers are paramount. The absence of proper energy transfer can result in consumer dissatisfaction, financial losses, and stagnation within the competitive economic market. Therefore, identifying the strengths and weaknesses of the transmission sector's performance and comparing regional electricity transmission companies can effectively help enhance the performance level of each.
One technique that has captured researchers' attention for evaluating the electricity industry's performance is the data envelopment analysis (DEA) technique. DEA is a non-parametric method used to assess the performance of homogeneous units, considering multiple inputs and outputs. It was initially introduced in 1978 by Charnes et al. The initial model was built upon the assumption of constant returns to scale. Subsequently, Banker et al. (1984) extended it by presenting a model under the assumption of returns to a variable scale.
Importantly, traditional DEA models evaluate a system's performance based on specific inputs and outputs consumed and produced by the unit. However, various factors, such as contextual variables, managerial ability, and skill, can significantly influence performance and productivity. A crucial point to consider is that managerial abilities are not always overtly visible. This lack of direct visibility can impede accurate measurement. Hence, recognizing these variables among the existing indicators and assessing their influence on the performance and efficiency of each unit holds particular significance. This procedure enhances the precision of evaluation and opens avenues for delivering enhanced solutions aimed at improving the system's overall performance.
Methodology
The objective of this study is to analyze and evaluate the performance of Iran's regional electricity transmission sector while considering contextual variables and establishing a ranking methodology based on managerial ability. This perspective enables the identification of strengths and weaknesses in the system's structure from various angles and offers appropriate solutions for enhancement. To accomplish this, the first step involves identifying all variables within the transmission section, encompassing inputs, outputs, and contextual factors. Subsequently, we determine the technical efficiency of each regional power transmission company, taking into account specific inputs and outputs, using meta-frontier technology. The concept of meta-frontier in DEA measures the gap or distance between decision-making units (DMUs) across different boundaries. This approach assumes a unified boundary for all subgroups, enabling efficiency estimation based on a single boundary (Battese, 2004; O'Donnell, 2008). Its primary advantage lies in resolving the challenge of evaluating efficiency at varying levels. As a result, meta-frontier technology enhances the precision of evaluating regional power companies over multiple periods. After assessing the efficiency of each regional electricity transmission company, we employ the linear regression method to estimate the impact of contextual variables on efficiency, subsequently yielding a measure of managerial ability. Ultimately, we introduce a method for ranking each company based on managerial ability. The advantage of the proposed method is that, in addition to reviewing and analyzing the technical efficiency of each of the companies in the regional electricity transmission sector during different periods, it will be possible to evaluate the managerial ability of each of the companies. Such a perspective allows for companies to be compared from different dimensions. Moreover, providing a new ranking criterion based on managerial ability also facilitates a better and more accurate comparison.
Results
In this study, the performance of Iran's regional power companies was analyzed and evaluated from two systems and management perspectives during the years 1390-1398. Additionally, a new rating criterion based on managerial ability was presented to compare the performance of companies during 9 time periods. In this regard, firstly, the technical efficiency of 16 regional electricity companies during 9 time periods was calculated based on the inputs of the number of employees and receiving energy from neighboring companies and the outputs of sending energy to neighboring companies and delivering energy to distribution companies, using meta-frontier technology and the DEA approach. Then, the effect of contextual variables, such as line length, transformer capacity, and loss magnitude, on the efficiency score of each company was estimated using the ordinary least squares method (OLS). Furthermore, the managerial ability of each company was determined during different periods. Ultimately, a ranking criterion was established based on the results of technical efficiency after removing the effect of contextual variables.
Conclusion
The results of efficiency measurements over 9 time periods indicate that the highest and lowest average efficiencies were observed in the years 1390 and 1398, respectively. Furthermore, it's evident that, in general, the performance of Iran's 16 regional electricity companies exhibited a consistent upward trend from 1390 to 1398. Among the 16 evaluated companies, the Guilan regional electricity company consistently achieved the highest level of efficiency across all 9 time periods, reflecting its strong performance. Conversely, the Fars regional electricity company consistently had the lowest efficiency, indicating its weaker performance compared to other companies. When analyzing the companies' performance by year, it's noteworthy that the Tehran regional electricity company secured the highest rank in 1390, 1391, and 1394, while the Fars regional electricity company held the top spot in the remaining years. In contrast, the Sistan regional electricity company consistently displayed the lowest performance throughout all periods. The assessment of management performance over the 9 time periods indicates that the Kerman regional electricity company demonstrated superior performance from 1390 to 1393, whereas the Guilan regional electricity company excelled from 1394 to 1398, outperforming other companies. Conversely, the Gharb regional electricity company exhibited weaker performance compared to its counterparts. Additionally, the results of the regression analysis highlight a positive relationship between the efficiency score and two variables: line length and transformer capacity. Conversely, the relationship with loss magnitude is observed to be inversely correlated.
Ali Mohtashami; Ali Fallahian-Najafabadi
Volume 11, Issue 31 , January 2014, , Pages 55-84
Abstract
In today’s competitive world, the organizations decide to establish competitive benefits by making benefit from management sciences. One of the most important management sciences arisen lots of so useful matters is the supply chain. The supply chain management is the evolved result of warehousing ...
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In today’s competitive world, the organizations decide to establish competitive benefits by making benefit from management sciences. One of the most important management sciences arisen lots of so useful matters is the supply chain. The supply chain management is the evolved result of warehousing management and is regarded as one of the infrastructure and important concepts for implementing the career so that in many of them it is essentially tried to shorten the time between the customer’s order and the real time of delivering the goods. Cross docking is one of the most important alternatives for lowering the time in supply chain. The central aim of this paper is to focus on optimizing the planning of the trucks input and output aiming to minimize total time of operation inside the supply chain in designed model. Timing the transportation in this paper makes the time between sources and destinations, time of unloading and transferring the products minimized. To find the optimum answers to the question, genetic algorithms and the particle swarm optimization have been used. Then, these algorithms have been compared with the standards such as the implementation time and quality of answers with each other and then better algorithms in each standard identified.
Seyyed Mohammad Aarabi; Reza Armanpoor
Volume 2, Issue 7 , December 2004, , Pages 57-81
Abstract
The present article is a result of application research in the field of improvement of bank services by the use of QFD method. QFD is means which translates actual nees of customers to specifications of product services. The needs of customers are gathered by a modern and structured method in QFD. Considering ...
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The present article is a result of application research in the field of improvement of bank services by the use of QFD method. QFD is means which translates actual nees of customers to specifications of product services. The needs of customers are gathered by a modern and structured method in QFD. Considering the organizational resources and capabilities of organization the needs or demands are answered.
With regard to the title of article the use of QFD technique in assessing of physical specifications of band branches the main purpose is to determine of customers points of view as to values which are expected of the quality of physical aspects of the branches. Also in the article we have compared the amount of answering to customer needs and expectations in refah band to other branches. Also in the article we have compared the amount of answering to customer needs and expectations in refah bank to other competitors as well as to assess their points of view as to required technical obligations and to design a proper pattern for assessing of physical specifications of the branches.
Considering the importance of marketing and selecting of the physical aspects and specifications among them we have interviewed customer and in order to determine their importance we have designed a questionnaire for customer based on the process of AHP. And we have assessed the technical specifications and obligations which will answer the needs by the help of expects and proficient in this field. Further we have determined the operation of band and its competitors in doing the desired needs of customers as well as their technical demands and obligations according to QFD technique in HOQ.
Finally we have presented the proper pattern acquired by the above matrix to assess the physical specifications for absolute branches of the Refah Bank.
Mohammad Reza Taghva; Hadi Esmaeilzadeh; Amir Mohtarami
Volume 3, Issue 9 , June 2005, , Pages 57-71
Abstract
Rapid development of applications of information technology in the third millennium and its enormous effects on the value chain of enterprises has imposed a strategic nature to this kind of technology. It is obvious that due to the influential role of information technology and its impact on enterprises ...
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Rapid development of applications of information technology in the third millennium and its enormous effects on the value chain of enterprises has imposed a strategic nature to this kind of technology. It is obvious that due to the influential role of information technology and its impact on enterprises we require to have a strategic view towards management of this technology.
In this paper we primarily introduce a brief history of the evolution of information technology and then we elaborate on the evolution of the various approaches of planning for information technology the main focus of each of the approaches in the planning process and various conditions and origins of every approach. These approaches are technological approach which focuses on efficiency alignment approach which focuses on change management and organizational change. Then we categorize and classify various information technology strategic planning models based on previously mentioned approaches of planning for information technology so that it can be helpful for information technology planners to choose their information technology strategic planning model based on an appropriate approach more conveniently.
mohammadamin nayebi; abouzar parsanejhad; mohammad reza parsanejhad
Volume 11, Issue 29 , July 2013, , Pages 61-87
Abstract
In this paper, we present a MCDM model for vendor selection of Telecommunications systems. Decision making in Telecommunications systems (Central) is more important because of their communicational role in organizations. Considering the multiple criteria in the vendor selection of telecommunications ...
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In this paper, we present a MCDM model for vendor selection of Telecommunications systems. Decision making in Telecommunications systems (Central) is more important because of their communicational role in organizations. Considering the multiple criteria in the vendor selection of telecommunications systems is a multi-criteria problem. Because these decisions usually are based on the intellectual judgments of managers, Fuzzy logic is used to improve decision making. Literature review and experts opinions used for determining the model indexes and then developed a Fuzzy TOPSIS model with combined weighs. Combined weights are result of integrating various methods such as intellectual judgment of managers, Fuzzy statistical average, modified weight and fuzzy weigh. In this model all numbers are Fuzzy and triangular type. A case study done in Qazvin Islamic Azad University to apply the developed model.
