One of the most important issues in area of health and hygiene is location-allocation of organ harvesting centers and transplant centers according to coordination between supply and demand. In this paper, a mathematic...
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One of the most important issues in area of health and hygiene is location-allocation of organ harvesting centers and transplant centers according to coordination between supply and demand. In this paper, a mathematical model is presented for location-allocation of organ harvesting centers and transplant centers. The proposed model does not only minimize the present value of the total system costs, but also minimizes the geographical inequalities. The presented model is a bi-objective nonlinear mathematical programming and some of the problem parameters, such as cost, transport time and the like are associated with uncertainty and considered as fuzzy sets in the mathematical formulation. In this paper, an Organ Transplant Supply Chain (OTSC) has been designed and the epsilon-constraint method has been used to solve the problem and Iran is considered as a case study. The results show that the patient's family satisfaction rate is more important than the viability rate in the number of transplant operations performed and for a transplant operation to be performed, the minimum satisfaction rate (beta(h)) should be 0.4 and organ viability rate (UDo) should be 0.2.
The operation of the electrical systems is a major problem for electrical companies' subject to uncertainties threatening. In this study, the optimal management of the energy demand in the electrical distribution ...
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The operation of the electrical systems is a major problem for electrical companies' subject to uncertainties threatening. In this study, the optimal management of the energy demand in the electrical distribution grid is done by interval optimization approach under electrical price uncertainty. The management of the energy demand is implemented via incentive-based modelling of the demand response programs (DRPs). The incentive-based modelling as reserve, and based on bid price for reduction of the electrical demand at peak hours is proposed. The interval optimization approach is used for the minimization of the electrical price uncertainty effects. The main objective in the proposed approach is minimizing operation cost;epsilon-constraint method is utilized to solve the problem. Finally, an electrical distribution grid has been used at various case studies to numerical simulation results and positive effects of the proposed modelling under uncertainties.
Using closed-loop supply chain network programming design to control carbon emissions is an important way that develop sustainable and environmentally conscious supply chains. This paper propose a multi-objective stoc...
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ISBN:
(纸本)9781538608432
Using closed-loop supply chain network programming design to control carbon emissions is an important way that develop sustainable and environmentally conscious supply chains. This paper propose a multi-objective stochastic programming model to cope with the strategic location and configuration problem of closed-loop supply chain. Besides the traditional profit maximization objective, the proposed model took the minimization of carbon emissions into consideration, and made a fair balance between them. Some parameters, such as customers demand and end of life product quantity, products sale price, production costs, operating costs, collection costs, disposal costs, etc. in this model are uncertain, therefore, a finite number of the possible scenarios was used to describe it. While it is a way to create more flexibility and real-world condition to use the uncertainty of parameters and multi-objective tradeoff. The epsilon-constraint method is applied to solve the proposed multi-objective model. Last a numerical example is tested and showed the stochastic model can reduce the uncertainty of parameters.
The conservation of lakes is an essential issue in sustainable development. Disruption of ecological balance, destruction of biodiversity and vegetation, desertification, and storm surges are the results of lakes dryi...
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The conservation of lakes is an essential issue in sustainable development. Disruption of ecological balance, destruction of biodiversity and vegetation, desertification, and storm surges are the results of lakes drying. The purpose of this paper is to introduce an integrated bi-objective sustainable water resource management model. The first objective function deals with economically optimal allocation of water to the residential, industrial, and agricultural sectors. For compliance with the requirements of sustainable development, the second objective is to maximize the amount of water allocated to the environment. For proper utilization and reuse of water resources, the location of urban wastewater treatment plants is also considered in the problem. The model is solved with data from the most important watershed in Iran, Urmia Lake. Natural and unnatural factors have dramatically reduced the amount of water intake and balance over the past two decades. The epsilonconstraint is used for solving the case study model. The results show that the model can satisfy the demand of sectors, with 70 percent of the available resources. The use of this model can meet the demands of the consumer sectors, and also, it can help revitalize Urmia Lake and the ecosystem of the river in its basin.
Due to the increasing amount of natural disasters such as earthquakes and floods and unnatural disasters such as war and terrorist attacks, Humanitarian Relief Chain (HRC) is taken into consideration of most countries...
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Due to the increasing amount of natural disasters such as earthquakes and floods and unnatural disasters such as war and terrorist attacks, Humanitarian Relief Chain (HRC) is taken into consideration of most countries. Besides, this paper aims to contribute humanitarian relief chains under uncertainty. In this paper, we address a humanitarian logistics network design problem including local distribution centers (LDCs) and multiple central warehouses (CWs) and develop a scenario-based stochastic programming (SBSP) approach. Also, the uncertainty associated with demand and supply information as well as the availability of the transportation network's routes level after an earthquake are considered by employing stochastic optimization. While the proposed model attempts to minimize the total costs of the relief chain, it implicitly minimize the maximum travel time between each pair of facility and the demand point of the items. Additionally, a data set derived from a real disaster case study in the Iran area, and to solve the proposed model a exact method called epsilon-constraint in low dimension along with some well-known evolutionary algorithms are applied. Also, to achieve good performance, the parameters of these algorithms are tuned by using Taguchi method. In addition, the proposed algorithms are compared via four multi-objective metrics and statistically method. Based on the results, it was shown that: NSGA-II shows better performances in terms of SNS and CPU time, meanwhile, for NPS and MID, MRGA has better performances. Finally, some comments for future researches are suggested.
This paper expects to give some guidelines for undergraduate students about how to implement environmental considerations in chemical process design and how the introduction of these issues could have an important eff...
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This paper expects to give some guidelines for undergraduate students about how to implement environmental considerations in chemical process design and how the introduction of these issues could have an important effect on the results obtained in the multiobjective problem optimization when economic and environmental aspects are considered simultaneously. For this work, a representative flowsheet of many chemical and petrochemical processes has been considered. This processing scheme works with a feedstock containing some inert and with not very high conversion per pass in the reactor. Therefore, the influence of the quality of raw materials, the installation of additional stages for treating effluents, the environmental impact and the optimum conversion of the chemical process are evaluated, attending both environmental and economic criteria. Our goals were, first to show how to identify the tradeoffs of a representative chemical process when environmental and economic considerations are included simultaneously in the design and its optimization. Secondly, how feedstock quality and additional waste treatment stages affect to the results obtained in the multiobjective optimization: minimize the total cost of the installation and its environmental impact. As a result, the final objective of this paper is to teach undergraduate students how multi-objective optimization could be used to make better decisions in the design of chemical processes, taking into account both economic (minimum total cost) and environmental (minimum environmental impact) performances. For each case study proposed, a detailed optimization was performed to determine Pareto curves using the epsilon-constraint method to identify the tradeoffs of this multiobjective optimization and ultimately determine the best alternatives, and even their optimum operational conditions attending to both criteria. It is important to remark that this problem could be solved in Excel so that it could be a good exam
This paper deals with the radial distribution system reconfiguration problem in a multi-objective scope, aiming to determine the optimal configuration by means of minimization of active power losses and several reliab...
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ISBN:
(纸本)9781467380416
This paper deals with the radial distribution system reconfiguration problem in a multi-objective scope, aiming to determine the optimal configuration by means of minimization of active power losses and several reliability indices. A novel way to calculate these indices under a mixed-integer linear programming (MILP) approach is provided. Afterwards, an efficient implementation of the ε-constraintmethod using lexicographic optimization is employed to solve the multi-objective optimization problem, which is formulated as a MILP problem. After the Pareto Efficient solution set is generated, a multi-attribute decision making procedure is used, namely the technique for order preference by similarity to ideal solution (TOPSIS) method, so that a decision maker (DM) can express preferences over the solutions and facilitate the final selection.
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