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Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

机译:利用混合模糊目标规划模型和混合遗传算法求解传染性垃圾处理的多目标定位路径问题

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摘要

Purpose: Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management.\udDesign/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move.\udFindings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively.\udOriginality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.
机译:目的:传染性废物的处置仍然是几乎每个国家在社会和环境领域中最严重的问题之一。选择新的合适位置并找到最佳的运输路线来运输传染性废物,即传染性废物处置的位置路由问题,是危险废物管理中的主要问题之一。\ udDesign / methodology / approach:由于该问题,案例研究中的位置路由问题,泰国次亚东北地区的40家医院和三个候选城市被分为两个阶段。第一阶段是使用混合模糊目标规划模型选择合适的城市,该模型将模糊层次分析法和模糊目标规划相结合。第二阶段是使用混合遗传算法找到每个选定城市的最佳路线,该算法将遗传算法与本地搜索(包括2-Opt-move,Inserting-move和?-interchange-move)进行混合。\ udFindings:结果表明,混合模糊目标规划模型可以指导新的合适城市的选择,并且混合遗传算法可以有效地为一组车队提供最佳路线。\ udOriginal / value:所提出的方法的新颖性,混合模糊目标规划模型是同时结合无形和有形因素以选择新的合适位置,并且可以使用混合遗传算法来确定最佳路线,从而在实际情况下有效地提供最少的车辆数量和最低的运输成本。

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