production and operations management
Mahsa Sobhi shojaa; Parvaneh Samouei
Abstract
In the recent years, robots have been widely used in assembly systems as called robotic assembly lines where a set of tasks have to be assigned to stations and each station needs to select one of the different robots to process the assigned tasks. Our focus is on u-type layouts because they are widely ...
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In the recent years, robots have been widely used in assembly systems as called robotic assembly lines where a set of tasks have to be assigned to stations and each station needs to select one of the different robots to process the assigned tasks. Our focus is on u-type layouts because they are widely employed in many industries due to their efficiency and flexibility . In these lines, a worker can be assigned to multiple stations located at entrance and exit sides. However, in many realistic situations, robots may be unavailable during the scheduling horizon for different reasons, such as breakdowns. This research deals with line balancing under uncertainty The Objective in this research is minimizing the cycle time for a given number of workstations and minimizing robot cost.This research deals with line balancing under uncertainty and presents one robust optimization model for balancing and sequencing of u-shaped robotic assembly line with considering set up times between task, failure robot times and preventive maintenance times for every robot. Since the NP-hard nature of the problem, multi-objective harmony search is developed to solve it. Numerical experiments also demonstrated that by increasing uncertainty level, the objective function values, cost and cycle times (minimum, maximum and average) increased. performance of the robust approach by the results, shows that in real conditions, considering the probability of event failure, values of cycle time and cost change significantly, which indicates the need to consider uncertainty, especially failure in robotic assembly lines.
Zahra Safari
Abstract
By increasing attention to environmental issues, the problem of design closed-loop supply chain has been more important. The integrated design of closed-loop supply chains as one of the most important issues in the management of supply chains involve determining the location and number of required facilities ...
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By increasing attention to environmental issues, the problem of design closed-loop supply chain has been more important. The integrated design of closed-loop supply chains as one of the most important issues in the management of supply chains involve determining the location and number of required facilities (production, collection, recycling and disposal) in the forward and reverse supply chain, inventories in every facility and flows between them. In this paper, a closed-loop supply chain with diverse products (multi-product) has been studied and a linear bi-objective mathematical model is proposed to reduce the total costs and the emissions in the network with determining the strategic and operational variables. Because of the uncertainty in parameters of proposed model such as customer demands or returns, the proposed model under uncertainty (robust optimization) is developed. The closed-loop supply chain of glass bottles is studied and modeled to minimize the total costs and production of carbon dioxide by proposed model. Finally, a sensitivity analysis of robust optimization model was conducted.
Adel Aazami; Ahmad Makui
Abstract
In this paper, multi-site aggregate production planning for the production of perishable products such as gifts of New Year, calendars and maturities by postponement policy in uncertainty conditions is determined. The production process for these products is proposed to be divided into two phases including ...
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In this paper, multi-site aggregate production planning for the production of perishable products such as gifts of New Year, calendars and maturities by postponement policy in uncertainty conditions is determined. The production process for these products is proposed to be divided into two phases including the production of final and semi-finished products with applying the concept of postponement. So, there are three production activities, including direct production, the production of semi-finished products and final assembly. Also, a robust optimization model to solve aggregate production planning problem for these products is developed. Finally, a set of real data from a calendar producing company in Tehran called “NIK Calendar” are used to validate and show the efficiency of the proposed model. Results show that the proposed model of this paper can use for similar factories which are active in the field of aggregate production planning with considering uncertainty in the parameters
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
Yalda Yahyazade; Laya Olfat; Maghsod Amiri
Abstract
Appropriate management of supply chain is one of the issues facing economic firms that affect all the organizational activities in order to produce the goods and provide the services. Consequently Supplier selection due to involvement of various qualitative and quantitative criteria such as quality, ...
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Appropriate management of supply chain is one of the issues facing economic firms that affect all the organizational activities in order to produce the goods and provide the services. Consequently Supplier selection due to involvement of various qualitative and quantitative criteria such as quality, price, flexibility and delivery times is very difficult and complex and requires accurate and appropriate tools. On the other hand today's competitive environment due to its variable nature, has added the uncertainty and ambiguity in decision-making. The problem of supplier selection is not an exception as well and it seems suitable to use the robust optimization methods in such circumstances. The mentioned method is used in this research with the goal of supplier selecting and determining the amount order of products considering all restrictions in order to minimize the costs and maximize the utility of purchase in the condition of uncertainty. In this paper, a multi-objective deterministic model is presented to solve the problem, and then the deterministic model is converted to the robust model using the scenario-based robust method and then is solved using the LP metric method so optimal amount of order is obtained from each of suppliers at any period. To determine the weight of each of suppliers, Analytical Hierarchy Process (AHP) is used as well.
Abas Fadaei; Masood Rabieh; Mostafa Zandieh
Abstract
Considering that the active companies in the field of oil, gas,petrochemical and other energies are project-based and also theincrease of gas applicants who have taken policy of replacing the gasinstead of other fossil fuels, have imposed certain condition onorganizations and project managers in the ...
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Considering that the active companies in the field of oil, gas,petrochemical and other energies are project-based and also theincrease of gas applicants who have taken policy of replacing the gasinstead of other fossil fuels, have imposed certain condition onorganizations and project managers in the Gas Company.One of themost important problem in the issue of project management is projectportfolio selection which is defined one of the most importantactivities in many organization such as gas organization. In this studyat first the effective indicators on projects are extracted by using theliterature and interviews with the experts of gas industry then themathematical robust multi objective model is provided by consideringthe uncertainty and unreliability in some parameters of model. Thismodel is solved by using Non-dominate Sorting Genetic Algorithmfor 20 degree of risk-taking decision Gama ( , Ct Bt ).At the end forhelping in decision making the TOPSIS technique is used forproviding a specific answer in Pareto Front .
Alireza Alinezhad; Niki Jalili Taghavian
Volume 13, Issue 39 , January 2016, , Pages 115-144
Abstract
Improving products quality and services is the best and most important factor to win competitors and get majority of the market share. In this regard, Failue mode and Effect analysis is an efficient tool to improve the quality products. Considering many criticisms to taraditional method, the risk priority ...
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Improving products quality and services is the best and most important factor to win competitors and get majority of the market share. In this regard, Failue mode and Effect analysis is an efficient tool to improve the quality products. Considering many criticisms to taraditional method, the risk priority number in FMEA is formed by multiplying of three factors (seveirity, Occurrence and Detect). In order to existing defects, a new method to calculate the risk priority number in FMEA based on data envelopment analysis method is introduced. The aim of this study is to provide a new kind of risk priority number by assigning different weights to each of the risk factors. Also according to severity, Occurance and detection numbers that are achieved by a team of experts and are not a constant and certain factor, in this research has been used Robust optimization because of covering the result of DEA and less complexity. The results of example indicate that, proposed model is more effective than traditional RPN and provide a full ranking.
Nafiseh Aghabozorgi; Seyed Mojtaba Sajadi; Mahdi Alinaghian
Volume 13, Issue 38 , October 2015, , Pages 99-132
Abstract
Today, field of production and service is faced with competition among the supply chains by changing the competition pattern of the independent companies. Most of the small and medium businesses (SMEs) still use traditional viewpoint for supply, production and distribution planning. It means, each of ...
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Today, field of production and service is faced with competition among the supply chains by changing the competition pattern of the independent companies. Most of the small and medium businesses (SMEs) still use traditional viewpoint for supply, production and distribution planning. It means, each of these SMEs plan their tasks independently, this will increase the total cost of the supply chain in many cases. In this study, a robust model of inventory-locating supply chain is proposed in three-level with uncertain demand. The model has been considered in single-period, multi-product state along with some transportation models with three levels of producers – distributors- retailers in certain and robust mode. Considering some transportation models along with robusting the model and the possibility of sending goods directly from the factory to the retailer is one of the innovations of this study. The objectives of the proposed model are to minimize the total cost of the three-leveled supply chain and to find the amount of safety stock. The certain model is solved by GAMS and the robust model is also solved by GAMS in single-objective mode and then transferred to the augmented ε-constraint method. The results have been discussed after solving the model.
Alireza Alinajad; Samrand Salari; Azadeh Seif
Volume 10, Issue 26 , January 2012, , Pages 123-146
Abstract
This research investigates issues relating to facilities location whichcovers network design under the conditions of uncertainty and robuststate. In this direction a model is developed in which lack of certaintyis taken into consideration regarding parameters such as demand andvarious costs. Unlike the ...
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This research investigates issues relating to facilities location whichcovers network design under the conditions of uncertainty and robuststate. In this direction a model is developed in which lack of certaintyis taken into consideration regarding parameters such as demand andvarious costs. Unlike the classical methods that the structure ofnetwork is predefined and is predetermined, the facilities locationmakes decisions with respect to the structure of the network.The discussed issue in many real and actual applications such as roadsnetwork, communication systems and etc does exist and locating thefacilities and designing the main network simultaneously areconsidered as important factors; therefore redesigning andoptimization of models which look for simultaneous solutions seemessential. There have been various strategies in the literature ofuncertainty optimization. Two of the most important strategies are the“Probabilistic Optimization” and “Robust Optimization”.This article employs the robust optimization to resolve the uncertaintyand the modelization arguments. Moreover using random samples, thedeveloped model is validated and for further mathematical analysis isutilized
