Improved Whale Optimization Algorithm via Cellular Automata
Yuchao Gao, Cheng Qian, Zhenghang Tao, Hu Zhou, Jinran Wu, Yang Yang · 2020
The idea of whale optimization algorithm comes from the unique hunting behavior of whales in the ocean. The whale optimization algorithm realizes the optimization of search by surrounding and attacking prey with bubbles. The algorithm has the characteristics of simple principles, good operation, easy implementation with few parameters and strong robustness. However, there are still some problems of its exploitation (convergence speed) in local space. To this end, we propose a new improved whale algorithm, which is based on cellular automata to find the optimal position, namely CA-WOA. Here, the cellular automata is introduced to enhance the local search ability and to speed up the convergence. According to experiments on seven benchmark functions and three truss design projects, we show that the proposed CA-WOA can obtain a better optimal solution with less computational cost.