University of Sussex
Browse
Swarm Intelligence Algorithm Inspired by Route Choice Behavior-v9.pdf (521.89 kB)

Swarm intelligence algorithm inspired by route choice behavior

Download (521.89 kB)
journal contribution
posted on 2023-06-09, 04:21 authored by Daxin Tian, Junjie Hu, Zhengguo ShengZhengguo Sheng, Yunpeng Wang, Jianming Ma, Jian Wang
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.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Journal of Bionic Engineering

ISSN

1672-6529

Publisher

Elsevier

Issue

4

Volume

13

Page range

669 - 678

Department affiliated with

  • Engineering and Design Publications

Research groups affiliated with

  • Sensor Technology Research Centre Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2016-12-06

First Open Access (FOA) Date

2017-11-10

First Compliant Deposit (FCD) Date

2016-12-06

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC