Multi-objective Variants of Water Strider Algorithm for Construction Engineering Optimization Problems
A. Kaveh, Ali Akbar Shirzadi Javid, Yasin Vazirinia
Abstract
Many engineering problems require optimizing multiple conflicting objectives simultaneously, necessitating efficient exploration of the design space for balanced solutions. The Water Strider Algorithm (WSA) is a robust metaheuristic technique that demonstrates superior performance compared to traditional evolutionary algorithms. This study evaluates two multi-objective variants of WSA: the Grid-based Multi-objective Water Strider Algorithm (GMOWSA) and the Non-dominated Sorting Water Strider Algorithm (NSWSA). Both variants incorporate a selection mechanism that archives and prioritizes high-quality solutions, emulating the natural behavior of water striders. The proposed methods are tested on nine multi-objective benchmark functions and three construction engineering optimization problems to assess their effectiveness. Comparative analysis against three state-of-the-art algorithms demonstrates that GMOWSA and NSWSA achieve competitive results, showcasing their potential for solving complex multi-objective optimization challenges in engineering applications.