Chaotic Wind Driven Optimization with Fitness Distance Balance Strategy

Abstract Wind driven optimization (WDO) is a meta-heuristic algorithm based on swarm intelligence. The original selection method makes it easy to converge prematurely and trap in local optima. Maintaining population diversity can solve this problem well. Therefore, we introduce new fitness-distance balance-based strategy replace the method, add chaotic search with selecting map memory further improve performance of algorithm. A wind balance proposed, called CFDBWDO. In experimental section, find optimal parameter settings for proposed To verify effect algorithm, conduct comparative experiments CEC 2017 benchmark functions. results denote that has superior performance. Compared WDO, CFDBWDO gradually function optimization. We practicality six real-world problems, obtained are all better than other algorithms.