Continuous optimization problem solution with simulated annealing and genetic algorithms

Abstract

Simulated Annealing (SA) and Genetic Algorithm (GA) are two well-known metaheuristic algorithms for combinatorial optimization. These two methods have also been used for solving constrained continuous problems. In this study, five constrained continuous problems have been solved both SA and GA. Optimum results have been compared with real optimum values obtained with continuous optimization methods. It has been seen that combinatorial optimization methods can successfully be applied to continuous optimization problems.