Nature-inspired metaheuristic optimization algorithms for urban transit routing problem

被引:3
作者
Li, Qian [1 ]
Guo, Liang [1 ]
机构
[1] Changchun Guanghua Univ, Coll Elect Informat Sch, Changchun 130000, Peoples R China
来源
ENGINEERING RESEARCH EXPRESS | 2023年 / 5卷 / 01期
关键词
UTNDP; urban transport; public transport; meta-heuristic; NETWORK DESIGN PROBLEM; MULTIOBJECTIVE OPTIMIZATION; GENETIC ALGORITHM; SEARCH ALGORITHM; BEE COLONY; STRATEGIES; SET;
D O I
10.1088/2631-8695/acbd87
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Designing urban transportation networks is a technological and social reality defined as a decentralized polynomial NP-Hard problem. In order to efficiently resolve this issue, several nature-inspired metaheuristic approaches have been proposed. Although these methods are crucial to resolving urban transportation network challenges, no comprehensive study has been conducted to address these concerns. Thus, this study provides an in-depth examination of nature-inspired metaheuristic methods applied to urban transmission. The current study aims to demonstrate the significant benefits of optimization algorithms in solving the Urban Transit Routing Problem (UTRP).
引用
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页数:13
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