The scientific fields dealing with day-to-day problems like economic planning and engineering design are mostly disconnected, high-dimensional, multimodal, and oscillated optimization problems. These complex problems cannot be solved well in reasonable time using conventional gradient-based processes. Natural phenomena and animal group behavior characteristics have motivated investigators to develop many efficient natural heuristic algorithms for high-dimensional complex optimization problems in the real world. This manuscript deals with one such meta-heuristic algorithm, Whale Swarm Optimization (WSO), and compares its performance with RMSProp optimization techniques. © 2021 Elsevier B.V., All rights reserved.