Modification of Bacterial Foraging Optimization Algorithm Using Elite Opposition Strategy

Abstract

This research work presents the modification of Bacterial Foraging Optimization Algorithm (BFOA) using the elite opposition strategy. The BFOA uses a random search strategy which affect it convergence performance due poor diversification in the search process and the possibility of Oscillatory behaviour towards the search process. The Elite Opposition BFOA is developed to provide more search space so as to enhance more exploitation. The Elite Opposition BFOA (EOBFOA) and the BFOA have been tested using twelve standard benchmark functions (Unimodal and Multimodal benchmark functions). From the simulation result obtained, the EOBFOA outperform BFOA by obtaining better global minimum solution.