[1]朱辰阳,赵春晓.个人快速交通动态任务分配问题的优化研究[J].计算机技术与发展,2022,32(11):127-133.[doi:10. 3969 / j. issn. 1673-629X. 2022. 11. 019]
　ZHU Chen-yang,ZHAO Chun-xiao.Research on Optimization of Dynamic Task Allocation in Personal Rapid Transit[J].,2022,32(11):127-133.[doi:10. 3969 / j. issn. 1673-629X. 2022. 11. 019]
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个人快速交通动态任务分配问题的优化研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年11期
页码:
127-133
栏目:
人工智能
出版日期:
2022-11-10

文章信息/Info

Title:
Research on Optimization of Dynamic Task Allocation in Personal Rapid Transit
文章编号:
1673-629X(2022)11-0127-07
作者:
朱辰阳1; 2 ; 赵春晓1; 2
1. 北京建筑大学 电气与信息工程学院,北京 100044;
2. 北京建筑大学 北京未来城市设计高精尖创新中心,北京 100044
Author(s):
ZHU Chen-yang1; 2 ; ZHAO Chun-xiao1; 2
1. School of Electrical and Information Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;
2. Beijing Future Urban Design Advanced Innovation Center,Beijing University of Civil Engineering and Architecture,Beijing 100044,China
关键词:
个人快速交通; 任务分配; 多智能体; 粒子群算法; NetLogo
Keywords:
personal rapid transit; task allocation; multi-agent; particle swarm optimization; NetLogo
分类号:
TP391. 9
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 11. 019
摘要:
个人快速交通(PRT) 是一种新型的公共交通工具。 由于此系统中的车辆仅在乘客需要时移动,因此这种特殊的按需特性会造成运输能力的高度浪费。 个人快速交通系统优化的目标是制定一个力求为所有行程请求提供服务的任务分配策略,在满足每辆车的电池容量的前提下,找到里程利用率和乘客等待时间之间的最佳权衡。 首先基于 NetLogo 平台建立了以里程利用率和乘客等待时间为优化目标的 PRT 系统多智能体模型,提出了一种基于淘汰机制的粒子群算法(EBPSO)求解系统中的动态任务分配问题。 所提算法在不损失里程利用率的前提下,相比标准粒子群算法使平均等待时间和最长平均等待时间分别降低了 47. 95% 和 41. 31% ;相比仅改进适应度函数的粒子群算法使平均等待时间和最长平均等待时间分别降低了 11. 17% 和 14. 85% 。 仿真结果表明,该算法在解决 PRT 车辆动态任务分配问题上与标准粒子群算法相比使系统效能大大提高。
Abstract:
Personal Rapid Transit ( PRT) is a new type of public transport. Because vehicles in this system move only when passengersneed it,this special on-demand feature can cause a high waste of transport capacity. The goal of the system optimization is to develop atask allocation strategy to provide services for all travel requests, and find the best balance between mileage utilization and passengerwaiting time on the premise of meeting the battery capacity of each vehicle. Firstly,based on NetLogo platform,a multi-agent model ofPRT system with mileage utilization and passenger waiting time as optimization objectives is established, and a particle swarmoptimization algorithm based on elimination mechanism ( EBPSO) is proposed to solve the dynamic task allocation problem in thesystem. Compared with the standard particle swarm optimization algorithm,the proposed algorithm reduces the average waiting time andthe longest average waiting time by 47. 95 % and 41. 31 % respectively without losing the mileage utilization rate. Compared with theparticle swarm optimization algorithm which only improves the fitness function,the average waiting time and the longest average waitingtime are reduced by 11. 17 % and 14. 85 % respectively. The simulation results show that the proposed algorithm greatly improves thesystem efficiency compared with the standard particle swarm algorithm in solving the dynamic task allocation problem of PRT vehicles.

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更新日期/Last Update: 2022-11-10