A hybrid ant-bee colony optimization for solving traveling salesman problem with competitive agents

Abba Suganda Girsang, Chun Wei Tsai, Chu Sing Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper presents a new method called hybrid ant bee colony optimization (HABCO) for solving traveling salesman problem which combines ant colony system (ACS), bee colony optimization (BCO) and ELU-Ants. The agents, called ant-bees, are grouped into three types, scout, follower, recruiter at each stages as BCO algorithm. However, constructing tours such as choosing nodes, and updating pheromone are built by ACS method. To evaluate the performance of the proposed algorithm, HABCO is performed on several benchmark datasets and compared to ACS and BCO. The experimental results show that HABCO achieves the better solution, either with or without 2opt.

Original languageEnglish
Title of host publicationMobile, Ubiquitous, and Intelligent Computing, MUSIC 2013
PublisherSpringer Verlag
Pages643-648
Number of pages6
ISBN (Print)9783642406744
DOIs
Publication statusPublished - 2014 Jan 1
Event4th International Conference on Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013 - Gwangju, Korea, Republic of
Duration: 2013 Sep 42013 Sep 6

Publication series

NameLecture Notes in Electrical Engineering
Volume274 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

Other4th International Conference on Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013
CountryKorea, Republic of
CityGwangju
Period13-09-0413-09-06

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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