Weighted multi-modal bat algorithm with improved search Online publication date: Mon, 20-Apr-2020
by Reshu Chaudhary; Hema Banati
International Journal of Hybrid Intelligence (IJHI), Vol. 1, No. 4, 2019
Abstract: Multi-modal bat algorithm with improved search (MMBAIS) is a variant of bat algorithm. MMBAIS incorporates foraging behaviour of bats by selecting prey based on possible energy gain (difference between energy gain and energy spent). This paper proposes a modification to MMBAIS: weighted MMBAIS (wMMBAIS), wherein movement pattern of bats is changed and a healthier diversity is maintained. wMMBAIS changes the method of prey selection by computing the net energy gain as a weighted difference of energy gain and energy spent. Exploration around best solution enhances efficiency of an algorithm. However, it may lead to diversity loss if not used carefully. To eliminate this drawback, wMMBAIS uses a weighted sum approach to perform exploration around the best solution. wMMBAIS is compared to BA, MMBAIS and nine other recent variants of BA, over 30 well-known optimisation functions. Results establish a significant improvement of the proposed variant over other algorithms.
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