基于细菌觅食优化算法的城市轨道交通调度优化
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摘要
为了合理高效地制定城市轨道交通调度方案,实现客流与车次的优化配置,提出了一种基于细菌觅食优化算法的城市轨道交通调度优化策略。兼顾乘客与运营企业双方利益,以发车间隔为决策变量,乘客平均候车时间最短和发车次数最少为优化目标,建立调度优化模型,并对细菌觅食优化算法求解该调度模型的过程进行分析。结合某城市轨道交通一号线实际运营数据进行仿真实验,并与其他算法的优化结果进行对比分析,实验表明该算法和模型能有效解决城市轨道交通调度优化问题。
In order to formulate a reasonable and effective dispatching scheme of urban rail transit and realize the optimal allocation of passengers flow and vehicles times,we propose an optimal urban rail transit scheduling based on the bacteria foraging optimization(BFO)algorithm.Taking into consideration the benefits of both enterprises and passengers and with departure interval as the variable,we establish an optimal model of dispatching and analyze the process of calculation and the solution to the model using the bacteria foraging optimization algorithm.The optimal targets are the shortest waiting time of passengers and a minimum quantity of dispatching vehicles.Stimulation experiments on the actual operation data of the No.1rail transit in a city show that the BFO algorithm and the dispatching model can solve the problem of urban rail transit optimization effectively.
In order to formulate a reasonable and effective dispatching scheme of urban rail transit and realize the optimal allocation of passengers flow and vehicles times,we propose an optimal urban rail transit scheduling based on the bacteria foraging optimization(BFO)algorithm.Taking into consideration the benefits of both enterprises and passengers and with departure interval as the variable,we establish an optimal model of dispatching and analyze the process of calculation and the solution to the model using the bacteria foraging optimization algorithm.The optimal targets are the shortest waiting time of passengers and a minimum quantity of dispatching vehicles.Stimulation experiments on the actual operation data of the No.1rail transit in a city show that the BFO algorithm and the dispatching model can solve the problem of urban rail transit optimization effectively.
引文
[1]Yao Chun,Li Mao-jun.The public transport dispatching problem and its partheno-genetic algorithm[J].Computer Engineering&Science,2011,33(11):75-79.(in Chinese)
[2]Wang Qing-rong,Yuan Zhan-ting,Zhang Qiu-yu.Study on transit scheduling optimization based on improved geneticsimulated annealing algorithm[J].Application Research of Computers,2012,29(7):2461-2463.(in Chinese)
[3]Fu A-li,Lei Xiu-juan.Intelligent dispatching of public transit vehicles using particle optimization algorithm[J].Computer Engineering and Applications,2008,44(15):239-241.(in Chinese)
[4]Wei Ming,Jin Wen-zhou,Sun Bo.Ant colony algorithm for regional bus scheduling problem[J].Journal of Highway and Transportation Research and Development,2011,28(6):141-145.(in Chinese)
[5]Li Zhi-yan.Research of public transportation scheduling based on PSO and ACO algorithms[D].Dalian:Dalian University of Technology,2013.(in Chinese)
[6]Passino K M.Biomimicry of bacterial foraging for distributed optimization and control[J].IEEE Control Systems Magazine,2002,22(3):52-67.
[7]Zhang Na.Study on job-shop scheduling problems based on bacteria foraging optimization algorithm[D].Changchun:Jilin University,2007.(in Chinese)
[8]Verma O P,Hanmandlu M,Kumar P,et al.A novel bacterial foraging technique for edge detection[J].Pattern Recognition Letters,2011,32(8):1187-1196.
[9]Daryabeigi E,Dehkordi B M.Smart bacterial foraging algorithm based controller for speed control of switched reluctance motor drives[J].International Journal of Electrical Power and Energy Systems,2014,62:364-373.
[10]Zhu Rui-jin,Wang Lian-guo.Node deployment strategy of WSNs based on BFO algorithm[J].Transducer and Microsystem Technologies,2014,33(9):128-131.(in Chinese)
[11]Lei Xiu-juan.Swarm intelligent optimization algorithms and their applications[M].Beijing:Science Press,2012.(in Chinese)
[12]Li jun,Dang Jian-wu,Bu Feng.Reseach and improvment of bacteria foraging optimization algorithm[J].Computer Simulation,2013,30(4):344-347.(in Chinese)
[13]Wang Lian-guo,Hong Yi,Zhao Fu-qing,et al.Improved artificial fish swarm algorithm[J].Computer Engineering,2008,34(19):192-194.(in Chinese)
[1]姚纯,李茂军.公交车辆优化调度问题及其单亲遗传算法[J].计算机工程与科学,2011,33(11):75-79.
[2]王庆荣,袁占婷,张秋余.基于改进遗传-模拟退火算法的公交排班优化[J].计算机应用研究,2012,29(7):2461-2463.
[3]付阿利,雷秀娟.粒子群优化算法在公交车智能调度中的应用[J].计算机工程与应用,2008,44(15):239-241.
[4]魏明,靳文舟,孙博.求解区域公交车辆调度问题的蚁群算法研究[J].公路交通科技,2011,28(6):141-145.
[5]李志延.基于粒子群与蚁群混合算法的公交调度研究[D].大连:大连理工大学,2013.
[7]张娜.细菌觅食优化算法求解车间调度问题的研究[D].长春:吉林大学,2007.
[10]朱瑞金,王联国.基于细菌觅食优化算法的WSNs节点部署策略[J].传感器与微系统,2014,33(9):128-131.
[11]雷秀娟.群智能优化算法及其应用[M].北京:科学出版社,2012.
[12]李珺,党建武,卜锋.细菌觅食优化算法的研究与改进[J].计算机仿真,2013,30(4):344-347.
[13]王联国,洪毅,赵付青,等.一种改进的人工鱼群算法[J].计算机工程,2008,34(19):192-194.
[2]Wang Qing-rong,Yuan Zhan-ting,Zhang Qiu-yu.Study on transit scheduling optimization based on improved geneticsimulated annealing algorithm[J].Application Research of Computers,2012,29(7):2461-2463.(in Chinese)
[3]Fu A-li,Lei Xiu-juan.Intelligent dispatching of public transit vehicles using particle optimization algorithm[J].Computer Engineering and Applications,2008,44(15):239-241.(in Chinese)
[4]Wei Ming,Jin Wen-zhou,Sun Bo.Ant colony algorithm for regional bus scheduling problem[J].Journal of Highway and Transportation Research and Development,2011,28(6):141-145.(in Chinese)
[5]Li Zhi-yan.Research of public transportation scheduling based on PSO and ACO algorithms[D].Dalian:Dalian University of Technology,2013.(in Chinese)
[6]Passino K M.Biomimicry of bacterial foraging for distributed optimization and control[J].IEEE Control Systems Magazine,2002,22(3):52-67.
[7]Zhang Na.Study on job-shop scheduling problems based on bacteria foraging optimization algorithm[D].Changchun:Jilin University,2007.(in Chinese)
[8]Verma O P,Hanmandlu M,Kumar P,et al.A novel bacterial foraging technique for edge detection[J].Pattern Recognition Letters,2011,32(8):1187-1196.
[9]Daryabeigi E,Dehkordi B M.Smart bacterial foraging algorithm based controller for speed control of switched reluctance motor drives[J].International Journal of Electrical Power and Energy Systems,2014,62:364-373.
[10]Zhu Rui-jin,Wang Lian-guo.Node deployment strategy of WSNs based on BFO algorithm[J].Transducer and Microsystem Technologies,2014,33(9):128-131.(in Chinese)
[11]Lei Xiu-juan.Swarm intelligent optimization algorithms and their applications[M].Beijing:Science Press,2012.(in Chinese)
[12]Li jun,Dang Jian-wu,Bu Feng.Reseach and improvment of bacteria foraging optimization algorithm[J].Computer Simulation,2013,30(4):344-347.(in Chinese)
[13]Wang Lian-guo,Hong Yi,Zhao Fu-qing,et al.Improved artificial fish swarm algorithm[J].Computer Engineering,2008,34(19):192-194.(in Chinese)
[1]姚纯,李茂军.公交车辆优化调度问题及其单亲遗传算法[J].计算机工程与科学,2011,33(11):75-79.
[2]王庆荣,袁占婷,张秋余.基于改进遗传-模拟退火算法的公交排班优化[J].计算机应用研究,2012,29(7):2461-2463.
[3]付阿利,雷秀娟.粒子群优化算法在公交车智能调度中的应用[J].计算机工程与应用,2008,44(15):239-241.
[4]魏明,靳文舟,孙博.求解区域公交车辆调度问题的蚁群算法研究[J].公路交通科技,2011,28(6):141-145.
[5]李志延.基于粒子群与蚁群混合算法的公交调度研究[D].大连:大连理工大学,2013.
[7]张娜.细菌觅食优化算法求解车间调度问题的研究[D].长春:吉林大学,2007.
[10]朱瑞金,王联国.基于细菌觅食优化算法的WSNs节点部署策略[J].传感器与微系统,2014,33(9):128-131.
[11]雷秀娟.群智能优化算法及其应用[M].北京:科学出版社,2012.
[12]李珺,党建武,卜锋.细菌觅食优化算法的研究与改进[J].计算机仿真,2013,30(4):344-347.
[13]王联国,洪毅,赵付青,等.一种改进的人工鱼群算法[J].计算机工程,2008,34(19):192-194.