Knowledge-Embedded Multi-Stage Genetic Algorithm for Interactively Optimizing a Large-Scale Distribution Network

May 2001

Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2001)

Volume

Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2001)

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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%) accuracy necessary. To realize the above requirements, a knowledge-embedded multi-stage GA method was developed. This method combines a high-speed GA with a knowledge-embedded GA having problem-oriented knowledge effective for some special location patterns. When conventional methods were applied, solutions for more than 20 cases out of 20000 cases were below expert-level accuracy. But the developed method could solve all of 20000 cases at expert-level.