Ramin Saedinia; Behnam Vahdani; Farhad Etebari; Behroz Afshar Nadjafi
Abstract
One of the most important approaches that can lead to the creation of various advantagesfor enterprises is the districting regions into the service offering locations and the demandunits, which causes the increase in level of customers’ access to get the service. On theother hand, if vehicle routing ...
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One of the most important approaches that can lead to the creation of various advantagesfor enterprises is the districting regions into the service offering locations and the demandunits, which causes the increase in level of customers’ access to get the service. On theother hand, if vehicle routing is carried out in districting regions in order to deliver productsto customers, the planning of customer service can be improved. However, in none of theresearch conducted in the area of design supply chain, vehicle routing in districting regionshas been not investigated. Therefore, in the current study, a bi-objective mathematicalmodel is presented to simultaneously focus on districting regions, facility location–allocation, service sharing, intra-district service transfer and vehicle routing. The firstobjective function minimizes the total cost of designing the CLSC network, which includescosts of opening facility and vehicle routing. The second objective function minimizes themaximum volume of surplus demand from service providers in order to achieve anappropriate balance in demand volume across all regions. Moreover, a robust optimizationapproach is used to take into account uncertainty in some parameters of the proposedmodel. In addition, the validity of the proposed mathematical model and the proposedsolution has been investigated on a real case in the oil and gas industry.
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 .
Mohammad Mahdi Bahrololoum; Mirfeiz Fallahshams; Ghasem Blue
Volume 13, Issue 39 , January 2016, , Pages 91-114
Abstract
In this study, the strategy of effective asset allocation under uncertainty with the capability of risk control, transaction cost reduction and favorable return realization is investigated. In order to implement this strategy and to overcome the shortfalls of classic portfolio optimization models in ...
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In this study, the strategy of effective asset allocation under uncertainty with the capability of risk control, transaction cost reduction and favorable return realization is investigated. In order to implement this strategy and to overcome the shortfalls of classic portfolio optimization models in dealing with uncertainty, the formation of an index fund using a robust approach and considering cardinality constraint became the agenda. Accordingly, in order to solve the index tracking problem, a linear programming model as minimizing the absolute deviation between the expected return of the index fund and that of the benchmark is presented. Considering the dimension of the solution space, a Meta heuristic genetic algorithm was implemented to solve the robust counterpart of the problem. The results of the analysis imply on the selection of 20 stocks as the index fund composition and indicate good performance of the index tracking funds based on criteria such as correlation, root mean square error and the excess return using out of sample data.
