A novel modified bat algorithm for global optimization

Bat algorithm (BA) is a recently introduced Meta-heuristic algorithm which mimics the echolocation behavior of micro-bats. In this paper, modified bat algorithm (MBA) is presented whose focus is to increase the exploration capability of BA and improve its consistency in finding global optima. The proposed version is tested on standard benchmark problems and is compared with standard state-of-art algorithms. Experimental results show that MBA is comparatively better than BA, flower pollination algorithm (FPA), differential evolution (DE) and bat flower pollinator (BFP).