A NEW EVOLUTIONARY BASED METAHEURISTIC ALGORITHM FOR UNCONSTRAINED OPTIMIZATION

Optimization problems naturally arise from many applications. We present a new metaheuristic algorithm that is a hybridization of a genetic algorithm and a variable neighborhood search for finding a global optimum of a function, without use of derivatives. We compare the efficiency of the proposed algorithm with a recently proposed variable neighborhood search. Results of computational experiments demonstrating both the effectiveness and the efficiency of our algorithm are reported.

کلیدواژه ها:

Hybrid metaheuristics ، Genetic algorithm ، Variable neighborhood search ، Unconstrained optimization