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.
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