详情

原文传递 Simultaneous Bus Transit Route Network and Frequency Setting Search Algorithm

题名：	Simultaneous Bus Transit Route Network and Frequency Setting Search Algorithm
正文语种：	英文
作者：	S. M. Hassan Mahdavi Moghaddam, Ph.D.1; K. Ramachandra Rao2; G. Tiwari3; Pravesh Biyani4
作者单位：	1Composants et Systèmes (COSYS), Génie des Réseaux de Transport Terrestres et Informatique Avancée (GRETTIA), Institut francais des sciences et technologies des transports, de l’aménagement et des réseaux, Universite Paris-Est, Marne-la-Vallee, Paris 77420, France (corresponding author). 2Professor, Dept. of Civil Engineering, Transportation Research and Injury Programme, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India. 3Professor, Dept. of Civil Engineering, Transportation Research and Injury Programme, Indian Institute of Technology Delhi, Room 815, 7th Floor Main Bldg., Hauz Khas, New Delhi 110016, India. 4Assistant Professor, Dept. of Electrical Engineering, Indraprastha Institute of Information Technology Delhi, New Delhi 110016, India.
关键词：	Bus route network design; Frequency setting; Genetic algorithm; Feasible regions; Transfer minimization operator; Mandl’s network
摘要：	A simultaneous bus route network design and frequency setting model is formulated as the weighted sum multiobjective genetic algorithm optimization. It aims to search for a near-optimum set of routes and corresponding frequencies while minimizing both user and operator costs. It is a nondeterministic polynomial time complete optimization problem, and searching the entire space through metaheuristic algorithms is impractical. It does require narrowing down the search space into some feasible regions. In this paper, two strategies are implemented, offering a distinct advantage in the finding of near-optimum solutions. First, a set of constraints are imposed on resources defined through experience and route generation and filtration algorithms are implemented to increase the quality of the candidate solution pool. Second, in order to increase the probability of selecting better performing set of routes and reducing genetic algorithm’s degree of randomness, a specially designed transfer minimization operator is implemented within the optimization procedure. Results are then compared on the basis of Mandl’s network that has been used as the benchmark by various researchers. Further, the sensitivity of the model to different rules and parameters is carried out. Obtained solutions perform better as compared to the previous techniques.
出版年：	2019
期刊名称：	Journal of Transportation Engineering
卷：	145
期：	4
页码：	1-14