A Novel Integrated Heuristic Optimizer Using a Water Cycle Algorithm and Gravitational Search Algorithm for Optimization Problems

Abstract

This paper presents a novel composite heuristic algorithm for global optimization by organically integrating the merits of a water cycle algorithm (WCA) and gravitational search algorithm (GSA). To effectively reinforce the exploration and exploitation of algorithms and reasonably achieve their balance, a modified WCA is first put forward to strengthen its search performance by introducing the concept of the basin, where the position of the solution is also considered into the assignment of the sea or river and its streams, and the number of the guider solutions is adaptively reduced during the search process. Furthermore, the enhanced WCA is adaptively cooperated with the gravitational search to search for new solutions based on their historical performance within a certain stage. Moreover, the binomial crossover operation is also incorporated after the water cycle search or the gravitational search to further improve the search capability of the algorithm. Finally, the performance of the proposed algorithm is evaluated by comparing with six excellent meta-heuristic algorithms on the IEEE CEC2014 test suite, and the numerical results indicate that the proposed algorithm is very competitive.