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

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. Categories and Subject Descriptors C.2.1 [Network Architecture and Design] General Terms Algorithms, Performance, Design Keywords Random Key-based Genetic Algorithm, Shortest Path Routing

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Mitsuo Gen, Lin Lin
• Keywords: GECCO 2006, Genetic Algorithm, Key-based Genetic Algorithm, Optimization, Shortest Path