Sustainable management of agricultural water resources is essential for promoting regional development and restoring ecological environment. Due to the imperfection of knowledge and imprecision of expression, the pref...
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Sustainable management of agricultural water resources is essential for promoting regional development and restoring ecological environment. Due to the imperfection of knowledge and imprecision of expression, the preferences of objectives are uncertain in nature. However, the uncertain feature of objective preferences is often neglected in solving multi-objective water management problems. Also, random information is prevalent in in the optimizaiton efforts of agricultural water management systems. Recognizing the needs to tackle uncertainty existing in both preferences over objectives and parameters of constraints, a new mathematical programming method named multi-objective chance-constrained programming approach for planning problems with uncertain weights (MCUW) was proposed. It could handle uncertain weights of objectives without known distributions, and quantify the risks of objective unattainability arising from such uncertainty. It could also deal with uncertain parameters with known probability distributions, generating solutions with varied risks of constraint violation. The proposed MCUW method was applied to a case study of agricultural water resources management problem in Northwest China to demonstrate its applicability. multiple sets of optimal solutions under different combinations of weights fluctuation ranges, protection levels, and surface water availabilities were obtained, providing management options for stakeholders with different risk appetites. Results indicate that the objective value would increase with higher risks of objective unattainability or water-shortage. The MCUW method was compared to two potential alternatives and deemed effective in balancing multiple objectives and tackling complex uncertainties. Monte Carlo simulation showed that the results of MCUW were more densely distributed than those obtained from the model with deterministic weights, verifying that the developed MCUW model could provide robust solutions when faced with
Trade-off problems concentrate on balancing the main parameters of a project as completion time, total cost and quality of activities. In this study, the problem of project time-cost-quality trade-off is formulated an...
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Trade-off problems concentrate on balancing the main parameters of a project as completion time, total cost and quality of activities. In this study, the problem of project time-cost-quality trade-off is formulated and solved from a new standpoint. For this purpose, completion time and crash cost of project are illustrated as fuzzy goals, also the dependency of implementing time of each activity and its execution-quality is described by a fuzzy number. The overall quality of the project execution is defined as the minimum execution-quality of the project activities that should be maximized. Based on some real assumptions, a three-objectiveprogramming problem associated with the time-costquality trade-off problem is formulated;then with the aim of identifying a fair and appropriate trade-off, the research problem is reformulated as a single objective linear programming by utilizing a fuzzy decision-making methodology. Generating a final preferred solution, rather than a set of Pareto optimal solutions, and having a reasonable interpretation are two most important advantages of the proposed approach. To explain the practical performance of the proposed models and approach, a time-cost-quality trade-off problem for a project with real data is solved and analyzed.
Electronic reverse logistics topic has received growing attention because of its environmental and economic impact. In Canada, the province of Ontario has enacted regulations regarding the Waste Electrical and Electro...
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Electronic reverse logistics topic has received growing attention because of its environmental and economic impact. In Canada, the province of Ontario has enacted regulations regarding the Waste Electrical and Electronic Equipment (WEEE) Recycling program. The objective of this study is to develop a novel scenario-based robust possibilistic approach to optimize and configure an electronic reverse logistics network by considering the uncertainty associated with fixed and variable costs, the quantity of demand and return, and the quality of returned products. A Monte Carlo simulation is utilized to analyze the performance of our proposed model. Then, ANOVA test is conducted to statistically verify our model using the simulation results. The mathematical model is extended to the multi-objective optimization by maximising the environmental compliance of the third parties. The efficient solutions of the multi-objective model are computed using the two-phase fuzzy compromise approach. To provide a comprehensive assessment of the problem under investigation, we provide sensitivity analyses on the impact of different factors (e.g., recovery rates, capacity of facilities) on the total expected profit. Several interesting results were obtained, including the fact that increasing the capacity of facilities does not automatically translate into higher profits. Furthermore, by comparing the efficient solutions of deterministic and robust modes, we illustrate the impact of robustness price on the multi-objective model. The application of the proposed model is illustrated using a network in the Greater Toronto Area (GTA) in Canada.
multi-objective transportation problem (MOTP) is a special case of vector minimization linear optimization problem with equality constraints and the objectives are conflicting in nature. Due to the conflicting nature ...
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This paper studies the biofuel logistics network scheme (BLNS) design problem dealing with several decision variables, such as the biofuel facility location, allocation, delivering harvested biomass stocks to biofuel ...
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This paper studies the biofuel logistics network scheme (BLNS) design problem dealing with several decision variables, such as the biofuel facility location, allocation, delivering harvested biomass stocks to biofuel producing facilities, and distributing biofuels to the stations. Since building the biofuel facilities requires a huge amount of investments, designing an efficient BLNS will be essential to attract potential investors. We formulate the design problem as a multi-objective programming (MOP) model. Solving the MOP model would yield various network schemes based upon the weight given to each objective/goal. Data envelopment analysis (DEA) method could be applied to evaluate the efficiency of each BLNS generated by solving the MOP model. Several approaches based on the traditional DEA method emerge to overcome a critical weakness regarding discriminating power. This paper combines three well-known DEA methods to make the most use of each method's strengths and to evaluate and identify the more efficient network schemes. Through a case study for South Carolina, we observe that the proposed procedure performs well in terms of designing efficient and robust BLNSs. The proposed procedure would enable the decision-makers to have more choices for BLNSs to consider before finally selecting the best scheme regarding efficiency, practicality, and feasibility. (C) 2020 Elsevier Ltd. All rights reserved.
In this paper, an uncertain multi-objectivemulti-item Solid Transportation Problem (MMSTP) based on uncertainty theory is presented. In the model, transportation costs, supplies, demands and conveyances parameters ar...
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In this paper, an uncertain multi-objectivemulti-item Solid Transportation Problem (MMSTP) based on uncertainty theory is presented. In the model, transportation costs, supplies, demands and conveyances parameters are taken to be uncertain parameters. There are restrictions on some items and conveyances of the model. Therefore, some particular items cannot be transported by some exceptional conveyances. Using the advantage of uncertainty theory, the MMSTP is first converted into an equivalent deterministic MMSTP. By applying convex combination method and minimizing distance function method, the deterministic MMSTP is reduced into single objectiveprogramming problems. Thus, both single objectiveprogramming problems are solved using Maple 18.02 optimization toolbox. Finally, a numerical example is given to illustrate the performance of the models.
In order to restore ecological function of wetland, determine the exploitation plan of water resources reasonably and promote the sustainable development of ecological function in wetland, based on the exploitation an...
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ISBN:
(纸本)9783037854167
In order to restore ecological function of wetland, determine the exploitation plan of water resources reasonably and promote the sustainable development of ecological function in wetland, based on the exploitation and utilization situation as well as the planning objectives of Panjin Shuangtai estuary wetland, this essay focuses on discussing water demand of natural ecological system, water quality of agricultural irrigation and aquaculture, and residential water consumption in wetland. Using various areas of wetland as decision variables and aiming to restore the size of all areas back to that in 2000, this essay takes the view of system engineering as guidance, establishes multi-objective programming model for rational allocation of wetland resources, and makes it able to compare with the other three created configurations plans. Results show that only giving priority to the needs of ecological water consumption of wetland to achieve an efficient use of surrounding water resources can we make the recovery of this wetland better and faster, and therefore achieve a desired sustainable development of ecological function. This has an important significance in leading us to a sustainable development of ecological restoration and constructing a framework of coordinated use of water resources of wetland system.
For establishing the city post-disaster emergency rescue shelter mechanism, the multi-objective programming is namely adopted for stationing and the emergency rescue shelter venues are prepared to arrange for fleeing ...
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ISBN:
(纸本)9781457720727
For establishing the city post-disaster emergency rescue shelter mechanism, the multi-objective programming is namely adopted for stationing and the emergency rescue shelter venues are prepared to arrange for fleeing victims. The present status and the progress of the traditional risk study are summarized, and then the multi-objective programming of distribution is used to in order to analysis the urban shelter optimally. The multi-objective approach is introduced to study the problems of the escape of evacuation stadium disaster, and then a multi-objective programming model is changed into an integer programming model to complete the stationing issues of post-disaster hedge places. The post-disaster hedge places entity optimization model is established by legitimately using multi-objective programming method, and the four targets, minimization shelter points for escaping, the minimization cost of investment, the maximization numbers of escape refugees and the fastest rate of escaping (the shortest time for arriving at escaping asylum points), are selected out to makes the distribution achieve the desired goals. And then an example is investigated to verify the feasibility of this method.
This paper presents a fuzzy goal programming approach to solve IT professionals' utilization problems for software firms. These problems involve multiple objectives and binary decision variables. The fuzzy goal pr...
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ISBN:
(纸本)9789811031564;9789811031557
This paper presents a fuzzy goal programming approach to solve IT professionals' utilization problems for software firms. These problems involve multiple objectives and binary decision variables. The fuzzy goal programming approach helps to quantify uncertainness of the objectives of the problem. With the help of membership functions, the problem is converted to its equivalent deterministic form. A case study demonstrates the effectiveness of the approach.
This paper presents an efficient method for solving a multiobjective bilevel programming problem with multiple number of objective functions in both first level as well as in second level. The uncertain parameters ar...
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This paper presents an efficient method for solving a multiobjective bilevel programming problem with multiple number of objective functions in both first level as well as in second level. The uncertain parameters are present in second level in form of fuzzy random variables. In this case the fuzzy random variables are assumed to be fuzzy normal random variables. First the fuzziness is removed by using alpha cut technique and randomness is removed by chance constrained method. Then multiobjective bilevel programming problem is transformed into a single objective non-linear mathematical model by using fuzzy programming technique. This non-linear mathematical model is solved by existing methodology or software. A numerical example is presented to illustrate the efficiency and feasibility of the proposed method.
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