The effect of GA parameters on the performance of GA-based QoS routing algorithm

Abstract

Genetic algorithm (GA) is a powerful search and optimization algorithm inspired by the theory of genetics and natural selection. However, the performance of GA depends largely on the values chosen for the GA parameters. In the previous work, a GA-based QoS routing algorithm for solving the multi-constrained path (MCP) problem has been developed. This paper presents the simulation result of the effect of three GA parameters which are maximum iterations, population size and mutation probability on the developed algorithm.