Affiliation:
1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing People's Republic of China
Abstract
AbstractImproving the sharing rate of public transport and reducing operation costs are key factors affecting the sustainable development of the public transport system. After quantifying the impact of transfer, this study proposes a multi‐objective optimization model of bus networks considering the integral transfer efficiency and operation costs, whose optimal solution is hard to find. Since the heuristic algorithm has great global searchability, a non‐dominated sorted genetic algorithm (NSGA‐II) is adopted to solve this NP‐hard problem. Also, an adaptive mutation mode selection algorithm is proposed to enhance the solution efficiency. The optimization framework is applied to the benchmark case of the Swiss public transit network. The results show that the method significantly improves the transfer efficiency of the designed network when compared to existing studies. After calculation, it is found that enhancing the direct rate can improve transfer efficiency, but with high costs. Moreover, the proposed method can design an efficient and economic network to balance the benefits of passengers and operators in practice.
Funder
National Natural Science Foundation of China
Publisher
Institution of Engineering and Technology (IET)
Subject
Law,Mechanical Engineering,General Environmental Science,Transportation
Cited by
3 articles.
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