Hybrid differential evolution and gravitation search algorithm for unconstrained optimization

Abstract

This paper proposed an algorithm called DE-GSA. The proposed algorithm incorporates both the concepts from Differential evolution algorithm (DE) and Gravitation search algorithm (GSA), updating particles not only by DE operators but also by GSA mechanisms. The proposed algorithm is tested on several benchmark functions including unimodal and multimodal test functions, multimodal test function with fix dimension, and some real life problems. Then, experimental results have shown that the proposed algorithm is both efficient and effective.   Key words: Gravitation search algorithm, differential evolution algorithm, differentialevolution with gravitation search algorithm (DE-GSA), hybrid meta-heuristic, algorithm.