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公交加气站选址布局优化模型和算法
引用本文:魏明,陈学武,孙博. 公交加气站选址布局优化模型和算法[J]. 交通运输系统工程与信息, 2015, 15(3): 160-165
作者姓名:魏明  陈学武  孙博
作者单位:1. 东南大学城市智能交通江苏省重点实验室,南京210096;2. 南通大学交通学院,江苏南通226019
基金项目:国家重点基础研究发展计划(973计划)资助项目(2012CB725402);中国博士后科学基金面上项目(2013M540408);江苏省高校自然科学研究面上项目(13KJB580008)
摘    要:针对不同线路的车辆加气需求在时间和空间上的不平衡性,将加气站抽象为多服务台排队系统,综合考虑车辆行驶、排队加气、加气站的位置对公交运营的影响等现实因素,以加气站的建设费用最小为第一目标,以极小化所有公交车的加气成本为第二目标,建立一种多目标公交加气站选址模型.根据问题特征,利用约束法,将之转化为单目标问题,设计求解该问题的遗传算法,定义解的编码方案、适应度函数、产生初始种群的启发式算法等.最后,结合一个算例,计算最佳的公交加气选址方案,分析加气站的能力对其布局的影响程度,从而验证模型和算法的有效性.

关 键 词:城市交通  加气站选址  车辆排队加气  多目标  遗传算法  
收稿时间:2014-09-05

Model and Algorithm for Bus Gas Station Site Layout Optimization Problem
WEI Ming , CHEN Xue-wu , SUN Bo. Model and Algorithm for Bus Gas Station Site Layout Optimization Problem[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(3): 160-165
Authors:WEI Ming    CHEN Xue-wu    SUN Bo
Affiliation:1. Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China; 2. School of Transportation, Nantong University, Nantong 226019, Jiangsu, China
Abstract:For the imbalance in time and space of refueling vehicles which belonged to different routes, a multiple objective model is studied for bus gas station site layout optimization to meet many realistic constraints such as vehicle’s travel, lining up to fuel at gas station, and influence of gas station’s location on bus operation, etc., by assuming that each gas station is looked as a multi-server queuing system. Previous objective is to minimize a total of cost for building gas stations, and secondary objective aims at minimizing fueling fee for all vehicles. According to characteristic of the model, it is converted into a single objective programming problem with constraint method. A design of genetic algorithm, which redesigns a solution coding, heuristic procedure to initialize chromosomes randomly, etc., is proposed to obtain the model’s noninferior solutions. Finally, a numerical example is taken to calculate its best scheme and analyze influence of gas station’s fueling capacity on them, which shows model and its algorithm’correctness and effectiveness.
Keywords:urban traffic  gas station site layout  all vehicles queuing for fueling at stations  multiple objective  genetic algorithm
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