Parallel Genetic Algorithms Based on a Multiprocessor System FIN and Its Application

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概要

• 論文の詳細を見る

• Genetic Algorithm (GA) is the method of approaching optimization problem by modeling and simulating the biological evolution. As the genetic algorithm is rather time consuming, the use of a parallel genetic algorithm can be advantage. This paper describes new methods for fine-grained parallel genetic algorithm using a multiprocessor system FIN. FIN has a VLSI-oriented interconnection network, and is constructed from a viewpoint of fractal geometry so that self-similarity is considered in its configuration. The performance of the proposed methods on the Traveling Salesman Problem (TSP), which is an NP-hard problem in the field of combinatorial optimization, is compared to that of the simple genetic algorithm and the traditional fine-grained parallel genetic algorithm. The results indicate that the proposed methods yield improvement to find better solutions of the TSP.

• 社団法人電子情報通信学会の論文
• 1995-11-25

著者

• TATSUMI Shoji

  Faculty of Engineering, Osaka City University

• KITAMURA Yasuhiko

  Faculty of Engineering, Osaka City University

• OKUMOTO Takaaki

  Faculty of Engineering, Osaka Institute of Technology

• Myung-Mook Han

  Faculty of Engineering, Osaka City University

• Han Myung-mook

  Osaka City University

• Kitamura Yasuhiko

  Faculty Of Engineering Osaka City University

• Tatsumi Shoji

  Faculty Of Engineering Osaka City University

• Tatsumi S

  Osaka City Univ. Osaka‐shi Jpn

• Okumoto T

  Osaka Institute Of Technology

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