An Improved Whale Optimization Algorithm Combined with Bat Algorithm and Its Applications

The whale optimization algorithm(WOA) is inspired by the hunting behavior of humpback whales. Due to its good effect in searching for optimal solutions, it has been applied to various problems such as engineering optimization, economic dispatch, and classification. However, when the WOA optimizes some complex problems, it may ignore global problem processing due to the selection of local optimal solutions, resulting in poor algorithm performance. This paper proposes an improved whale optimization algorithm combined with the bat algorithm(WOACBA) to solve global optimization problems. The test results of the algorithm on the CEC2014 benchmark function verify that it is superior to other comparison algorithms on the test function. It is applied to the mathematical modeling of welded beam design, the results show that WOACBA achieved relatively good application results in solving engineering application problems.