Novel ant colony optimization algorithm with path crossover and heterogeneous ants for path planning

Joon Woo Lee, Ju Jang Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

In this paper, a novel ACO algorithm is proposed to solve the global path planning problems, called Heterogeneous ACO (HACO) algorithm. We study to improve the performance and to optimize the algorithm for the global path panning of the mobile robot. The HACO algorithm differs from the Conventional ACO (CACO) algorithm for the path planning in three respects. We modify the Transition Probability Function (TPF) and the Pheromone Update Rule (PUR). In the PUR, we newly introduced the Path Crossover (PC). We also propose the first introduction of the heterogeneous ants in the ACO algorithm. In the simulation, we apply the proposed HACO algorithm to general path planning problems. At the last, we compare the performance with the CACO algorithm.

Original languageEnglish
Title of host publicationProceedings - ICIT 2010
Subtitle of host publicationIEEE-ICIT 2010 International Conference on Industrial Technology
Pages559-564
Number of pages6
DOIs
StatePublished - 2010
EventIEEE-ICIT 2010 International Conference on Industrial Technology, ICIT 2010 - Vina del Mar, Chile
Duration: 14 Mar 201017 Mar 2010

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology

Conference

ConferenceIEEE-ICIT 2010 International Conference on Industrial Technology, ICIT 2010
Country/TerritoryChile
CityVina del Mar
Period14/03/1017/03/10

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