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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Optimal Facility Location Model Based on Genetic Simulated Annealing Algorithm for Siting Urban Refueling Stations
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Optimal Facility Location Model Based on Genetic Simulated Annealing Algorithm for Siting Urban Refueling Stations

机译:基于遗传模拟退火算法的城市加油站设施最优选址模型

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This paper analyzes the impact factors and principles of siting urban refueling stations and proposes a three-stage method. The main objective of the method is to minimize refueling vehicles’ detour time. The first stage aims at identifying the most frequently traveled road segments for siting refueling stations. The second stage focuses on adding additional refueling stations to serve vehicles whose demands are not directly satisfied by the refueling stations identified in the first stage. The last stage further adjusts and optimizes the refueling station plan generated by the first two stages. A genetic simulated annealing algorithm is proposed to solve the optimization problem in the second stage and the results are compared to those from the genetic algorithm. A case study is also conducted to demonstrate the effectiveness of the proposed method and algorithm. The results indicate the proposed method can provide practical and effective solutions that help planners and government agencies make informed refueling station location decisions.
机译:本文分析了城市加油站选址的影响因素和原理,提出了一种三阶段法。该方法的主要目的是最大程度地减少加油车辆的tour回时间。第一阶段旨在确定加油站选址中最常行驶的路段。第二阶段着重于增加额外的加油站,以服务那些其需求并未由第一阶段中确定的加油站直接满足的车辆。最后阶段进一步调整和优化由前两个阶段生成的加油站计划。提出了一种遗传模拟退火算法来解决第二阶段的优化问题,并将结果与​​遗传算法的结果进行比较。还进行了案例研究,以证明所提出的方法和算法的有效性。结果表明,所提出的方法可以提供实用有效的解决方案,帮助规划人员和政府机构做出明智的加油站位置决策。

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