Mohammad Ali Khatami Firoozabadi; Abbas Abbasiazar; Mohammad Reza Taqva; kamran feizi
Abstract
AbstractIn this paper, a model for evaluating electronic services in nonprofit institutions is presented. The idea of this model was due to a vacuum of research in this field. Regarding this issue, independent variables have been extracted from the perspective of members of the research community for ...
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AbstractIn this paper, a model for evaluating electronic services in nonprofit institutions is presented. The idea of this model was due to a vacuum of research in this field. Regarding this issue, independent variables have been extracted from the perspective of members of the research community for the evaluation of electronic services based on inductive method and fundamental conceptualization theory. These variables include governance issues, tools, and customers.Indicators for measuring two variables of government and a measurable tool refer to financial systems and based on cost accounting methodology. However, it was not possible to determine the amount (rials) of the customer variable in this way. Therefore, a process was developed using existing theoretical foundations, including the relative estimation method for accounting, the Delon and McLean evaluation model, and the value engineering and how these two variables influence the management and tools. Then, in order to test the model and development process, the municipality of Tehran decided to evaluate the electronic license of the traffic plan. The result of determining the value of electronic services allows the use of this model in real terms
shaghayegh Vaziri; Arash Zaretalab; Mani Sharifi
Abstract
Course timetabling problem is a weekly assignment a set of course and teacher to the time and space with considering a lot of hard and soft constraints in universities. In each semester, heads of educational institutes take too much time and effort to prepare a timetable by using trial and error method ...
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Course timetabling problem is a weekly assignment a set of course and teacher to the time and space with considering a lot of hard and soft constraints in universities. In each semester, heads of educational institutes take too much time and effort to prepare a timetable by using trial and error method or last semester's timetable, although the rapid changing needs, resources and rules of each semester causes this method are not the perfect solutions. In this study, we design and develop a novel multi objective mathematical model which taking into account the preferences of students and teachers, Due to the complexity, we have benefited the metaheuristic algorithm to solve nonlinear model. Simulated Annealing algorithm is used to solve the mathematical model in two stages. In the first stage, the system automatically generates feasible solutions that will meet all the hard constraints. Then, the solutions are improved with spotting different neighborhood's structures. This collection is in the form of computer software application which is implemented the C# language programing and SQL database. This system is tested the data gathered by Azad University data and the results compared to the manual process showed the great progress is achieved. The entire system is flexible and easy to test different scenarios
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.
Alireza Rashidi Komijan; Amin Gordani
Abstract
The problem of Airline planning has totally been divided into four sub-problems.These problems include Flight Scheduling, Fleet Assignment, Aircraft Routing, Maintenance, and Crew Scheduling. In this research, firstly, we defined basic concepts and common terminology about Airline Planning then early ...
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The problem of Airline planning has totally been divided into four sub-problems.These problems include Flight Scheduling, Fleet Assignment, Aircraft Routing, Maintenance, and Crew Scheduling. In this research, firstly, we defined basic concepts and common terminology about Airline Planning then early models and previous researchers were presenting investigated articles. Moreover, by identifying existing research gaps, an Integrated Mathematical model presented for Aircraft Routing and Crew Scheduling for Airlines with Multi Fleet and Multi Maintenance hub with considering the rules of the Airlines. The main purpose of the proposed model is to determine the flight chains for each aircraft and crew assignments to all aircrafts with the attention to the airlines rules and regulations for aircrafts and crew. In the integrated models by previous researcher in this field, usually the type of fleet is considered the same while in the model presented in this research, the type of fleet is considered different. Other innovations of this research consider several maintenance units for an airline. In addition, the minimizations of deadheading flights for crew and aircraft that can impose heavy costs to the airline is presented as a part of the objective function in the model presented. Finally, the problem has been solved into small dimensions by GAMS software and in order to solve it in the larger dimensions a meta-heuristic method is being used, such as genetics algorithm. At the end, we have presented the results, which came from meta-heuristic Algorithm and GAMS Software.
Arman Sajedinejad; Meysam Lotfi
Abstract
In this paper, a non-periodic preventive maintenance scheduling optimization model for multi-component systems is provided based on the maximum availability of system components. In addition to providing the required level of system reliability and satisfy other system constraints (maintenance activities ...
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In this paper, a non-periodic preventive maintenance scheduling optimization model for multi-component systems is provided based on the maximum availability of system components. In addition to providing the required level of system reliability and satisfy other system constraints (maintenance activities and available resources), total costs (direct and indirect) associated with minimal maintenance and, if necessary, one of the maintenance activities include in inspected and serviced simple, preventive repair and preventive replacement for each component, is proposed. Each of these activities uses various sources and regarding the position of the repairing component, effects differently on the reliability of the system. The costs considered include in direct costs (simple service, repair and replacement) as well as indirect costs (out of order and random failures). Since the proposed model has a complex structure, in order to solve the problem, the Genetic Algorithm (G.A) has been used and the results is presented. In the end, performance and use of this model, for a 10-part series - parallel is presented in the form of a case study.
amir daneshvar; Mahdi Homayounfar; elham akhavan
Abstract
Data classification is one of the main issues in management science which took into account from different approaches. Artificial intelligence methods are among the most important classification methods, most of them consider total accuracy function in performance evaluation. Since in imbalanced data ...
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Data classification is one of the main issues in management science which took into account from different approaches. Artificial intelligence methods are among the most important classification methods, most of them consider total accuracy function in performance evaluation. Since in imbalanced data sets this function considers the cost of prediction errors as a fix amount, in this research a sensitivity function in used in addition to the accuracy function in order to increase the accuracy in all of the predefined classes. In addition, due to complexity in process of seeking information from decision maker, NSGA II algorithm is used to extract the parameters (Weight vector and cut levels between classes). In each iteration, based on the estimated weight vector and data sets, the algorithm calculate the score of each alternative using Sum Product function and then allocates the alternative to one of the classes, comparing to the estimated cut levels,. Then, using the fitness functions, the estimation class and the actual class will compare by two algorithms and this process will continue since optimizing the parameters. Comparison of the NSGA II and NRGA algorithms show the high efficiency of the proposed algorithm.
Moslem Peymany Foroushany; Amir Hossein Erza; maryam hamidizadeh; Mahdi Asgharzadeh
Abstract
The formation of the optimum portfolio based on risk and return is one of the most important decisions of investors in financial markets, for which there are various methods. Markowitz’s Mean-Variance method was the first method introduced in this area; but because of the normality assumption for ...
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The formation of the optimum portfolio based on risk and return is one of the most important decisions of investors in financial markets, for which there are various methods. Markowitz’s Mean-Variance method was the first method introduced in this area; but because of the normality assumption for the return distribution function, it only considered specific characteristics (expected return and variance) of the return distribution function. Another method introduced years later was the Stochastic Dominance method which considers all of the return distribution function instead of specific characteristics such as variance. The present research investigates the “Stochastic Dominance method” in portfolio optimization and compares the performance of this method with “Markowitz Portfolio Optimization method” using performance evaluation criteria in the Tehran Stock Exchange. The performance evaluation criteria used in this article are: Sharpe, Treynor, Sortino and Omega. The results of this research indicate the advantage of Second Order Stochastic Dominance method on the Markowitz method in out-of-sample and in-sample approaches. Moreover the Second Order Stochastic Dominance method has a higher cumulative return than the Markowitz method.
hamidreza jafari; parivash torki
Abstract
Since the acquisition of the market share is a correlational parameter, (the sum of the total market share of the competing organizations must be 100 percent) and the maximum in the present study, a DEA-based mathematical model was proposed to specify the competition strategies considering the correlational ...
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Since the acquisition of the market share is a correlational parameter, (the sum of the total market share of the competing organizations must be 100 percent) and the maximum in the present study, a DEA-based mathematical model was proposed to specify the competition strategies considering the correlational parameters and the magnitude and dimensions of insurance organizations. To examine the efficiency and the reliability of the proposed model, a real problem was solved in the domain of insurance industry and the results were compared with those of the basic CCR model. The findings revealed that the use of the basic CCR model to solve the problem produces unrealistic results that contradict the conditions and constraints of the real world. This was the case despite the fact that the proposed model proved more efficient and the results suggested that the proposed model improved the weaknesses of the basic DEA models in the domain of insurance institutes
Reza Abbasi
Abstract
Nowadays, most of the holdings and contracting companies are based on their projects, so most of their revenues depend on the selection and proper implementation of the projects. Basically, evaluating and selecting projects to form an optimal portfolio of an organization's project is a multi-criteria ...
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Nowadays, most of the holdings and contracting companies are based on their projects, so most of their revenues depend on the selection and proper implementation of the projects. Basically, evaluating and selecting projects to form an optimal portfolio of an organization's project is a multi-criteria decision-making problem that has uncertainty and ambiguity, depending on its nature and the judgments of decision makers. Hence, managers need systematic mechanisms to make the right decisions in the presence of multiple criteria. In this paper, an integrated framework based on Fuzzy function performance expansion and the Fuzzy Network Analysis process approach is proposed to revert the requirements of employers to the required technical characteristics as well as to evaluate and select candidate projects for entry into the project portfolio of the organization. To demonstrate the capabilities of the proposed framework, the evaluation and selection of the most suitable project in the field of building and construction was carried out in a project-based project company. The results indicate that among the requirements of the employers in this area, "systematic project risk management" of the highest importance (weight) and among the technical characteristics of the project (project evaluation criteria), "technology capability" with a score of 0.088 is more important than other Metrics. In addition, the proposed Fifth Project, in aggregate, has all the highest scores and serves as a candidate project.
Ardeshir Ahmadi
Abstract
This paper presents a scenario-based multistage stochastic programming model to deal with multi-period portfolio optimization problem with cardinality constraints and proportional transaction costs. The presented model aims to minimize investor's expected regret, while setting a minimum level of expected ...
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This paper presents a scenario-based multistage stochastic programming model to deal with multi-period portfolio optimization problem with cardinality constraints and proportional transaction costs. The presented model aims to minimize investor's expected regret, while setting a minimum level of expected return. To generate the scenario tree of stochastic parameters, a random walk model based on Johnson transformation and a sampling procedure is used. To implement the scenario tree generation method, historical returns of 28 domestic indices are used. Then, the scenario tree of stochastic parameters are used to solve the proposed multistage stochastic programming model. In addition, the impact of transaction costs, minimum expected returns and predetermined target wealth are investigated. Numerical results show that transaction costs, minimum expected returns and target wealth have a direct impact on expected regret. Finally, back testing simulation is used to assess and analyze the impact of the proposed approach in a dynamic, multi-period setting.
