Swarm intelligence algorithm inspired by route choice behavior

Tian, Daxin, Hu, Junjie, Sheng, Zhengguo, Wang, Yunpeng, Ma, Jianming and Wang, Jian (2016) Swarm intelligence algorithm inspired by route choice behavior. Journal of Bionic Engineering, 13 (4). 669 - 678. ISSN 1672-6529

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Abstract

Abstract Travelers' route choice behavior, a dynamical learning process based on their own experience, traffic information, and influence of others, is a type of cooperation optimization and a constant day-to-day evolutionary process. Travelers adjust their route choices to choose the best route, minimizing travel time and distance, or maximizing expressway use. Because route choice behavior is based on human beings, the most intelligent animals in the world, this swarm behavior is expected to incorporate more intelligence. Unlike existing research in route choice behavior, the influence of other travelers is considered for updating route choices on account of the reality, which makes the route choice behavior from individual to swarm. A new swarm intelligence algorithm inspired by travelers' route choice behavior for solving mathematical optimization problems is introduced in this paper. A comparison of the results of experiments with those of the classical global Particle Swarm Optimization (PSO) algorithm demonstrates the efficacy of the Route Choice Behavior Algorithm (RCBA). The novel algorithm provides a new approach to solving complex problems and new avenues for the study of route choice behavior.

Item Type: Article
Keywords: mathematical optimization
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Research Centres and Groups: Sensor Technology Research Centre
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TA Engineering (General). Civil engineering (General) > TA0164 Bioengineering
Depositing User: Zhengguo Sheng
Date Deposited: 06 Dec 2016 10:41
Last Modified: 11 Sep 2017 05:37
URI: http://srodev.sussex.ac.uk/id/eprint/65827

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