Modified Shuffled Multi-Population Bat Algorithm

摘要

Shuffled Multi-Population Bat algorithm (SMPBat) is a recently proposed hybrid variant of bat algorithm. It incorporates the strengths of two recent variants of bat algorithm-Enhanced Shuffled Bat Algorithm and Bat algorithm with Ring Master-Slave strategy. SMPBat hybridizes the sub-population generation and manipulation mechanism of the two algorithms to device an enhanced variant of BA. There are multiple parameters controlling the flow of execution of SMPBat. These parameters are set at the beginning of the execution of the algorithm. This paper proposes incorporation of multi-parameter setting into SMPBat, where different sub-populations work with different sets of parameter values. Additionally, the impact of a refined search mechanism is also studied. The proposed variants are tested over 20 benchmark functions and a real-world optimization problem. Results establish the robustness of the proposed work.