A new approach for shortest path routing problem by random key-based GA

  • Authors:
  • Mitsuo Gen;Lin Lin

  • Affiliations:
  • Waseda University, Kitakyushu, JAPAN;Waseda University, Kitakyushu, JAPAN

  • Venue:
  • Proceedings of the 8th annual conference on Genetic and evolutionary computation
  • Year:
  • 2006

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Abstract

In this paper, we propose a Genetic Algorithm (GA) approach using a new paths growth procedure by the random key-based encoding for solving Shortest Path Routing (SPR) problem. And we also develop a combined algorithm by arithmetical crossover, swap mutation, and immigration operator as genetic operators. Numerical analysis for various scales of SPR problems shows the proposed random key-based genetic algorithm (rkGA) approach has a higher search capability that enhanced rate of reaching optimal solutions and improve computation time than other GA approaches using different genetic representation methods.