Solving multi-objective optimization problems by RasID-GA

This paper aims to solve multi-objective problems by adaptive random search with intensification and diversification combined with genetic algorithm (RasID-GA). Problems with multi-objectives are common in engineering, economics, computer science, and many others field of studies. It has been a challenge for the researchers to develop algorithms able to solve this kind of problem. RasID is an optimization algorithm, which is good at finding local optima, but its diversified search isnpsilat so efficient, for this reason, we combined RasID with genetic algorithms (GA), which is superior at finding global optima. In this paper, RasID-GA is used to find the Pareto- optimal solutions. RasID-GA is compared with the algorithm of NSGA-II using well known benchmarks.