A Simple and Global Optimization Algorithm for Engineering Problems: Differential Evolution Algorithm

Authors : Derviş KARABOĞA

Pages : 53-60

View : 22 | Download : 7

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :Differential Evolution insert ignore into journalissuearticles values(DE); algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum regardless of the initial parameter values, fast convergence, and using few control parameters. DE algorithm is a population based algorithm like genetic algorithms using similar operators; crossover, mutation and selection. In this work, we have compared the performance of DE algorithm to that of some other well known versions of genetic algorithms: PGA, Grefensstette, Eshelman. In simulation studies, De Jong`s test functions have been used. From the simulation results, it was observed that the convergence speed of DE is significantly better than genetic algorithms. Therefore, DE algorithm seems to be a promising approach for engineering optimization problems.
Keywords : Optimization, Genetic Algorithm, Differential Evolution, Test Functions