A Multi-step Intelligent Genetic Algorithm to Optimize Delivery Problem within Interactive-time

To optimize large-scale distribution networks, solving about 1000 (around 40 cities) TSPs (Traveling Salesman Problems) within an interactive length of time (max. scores of seconds) is required. Yet, expert-level (less than 3% of errors) accuracy is necessary. To realize the above requirements, a Mu...

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Bibliographic Details
Published inJournal of Japan Society for Fuzzy Theory and Intelligent Informatics Vol. 20; no. 4; pp. 639 - 652
Main Authors ONOYAMA, Takashi, TSURUTA, Setsuo, KUBOTA, Sen, SAKURAI, Yoshitaka
Format Journal Article
LanguageJapanese
Published Japan Society for Fuzzy Theory and Intelligent Informatics 15.08.2008
Subjects
GA (Genetic Algorithm)
Heuristics
TSP (Traveling Salesman Problem)
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Summary:To optimize large-scale distribution networks, solving about 1000 (around 40 cities) TSPs (Traveling Salesman Problems) within an interactive length of time (max. scores of seconds) is required. Yet, expert-level (less than 3% of errors) accuracy is necessary. To realize the above requirements, a Multi-step intelligent GA method was developed. This method combines a high-speed GA with an intelligent GA holding problem-oriented knowledge that is effective for some special location patterns. If conventional methods were applied, solutions for more than 20 out of 20,000 cases were below expert-level accuracy. However, the developed method could solve all of 20,000 cases at expert-level.
ISSN:1347-7986
1881-7203
DOI:10.3156/jsoft.20.639