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A Multi-world Intelligent Genetic Algorithm to Interactively Optimize Large-scale TSP

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5 Author(s)
Yoshitaka Sakurai ; School of Information Environment, Tokyo Denki University., 2-1200 Muzai Gakuendai Inzai, Chiba, 270-1382, Japan. ysakurai@sie.dendai.ac.jp ; Takashi Onoyama ; Sen Kubota ; Yoshihiro Nakamura
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To optimize large-scale distribution networks, solving about 1000 middle scale (around 40 cities) TSPs (traveling salesman problems) within an interactive length of time (max. 30 seconds) is required. Yet, expert-level (less than 3% of errors) accuracy is necessary. To realize the above requirements, a multi-world 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

Published in:

2006 IEEE International Conference on Information Reuse & Integration

Date of Conference:

16-18 Sept. 2006