Multi-Objective Water Strider Algorithm for Complex Structural Optimization: A Comprehensive Performance Analysis

For various daunting physical world structural optimization design problems, a novel multi-objective water strider algorithm (MOWSA) is proposed, and its non-dominated sorting (NDS) framework is explored. This effort is inspired by the recent proposals for the Water Strider Algorithm, a population-based mathematical paradigm focused on the lifespan of water strider insects. The crowding distance characteristic is integrated into MOWSA to improve the exploration and exploitation trade-off behavior during the advancement of the quest. Furthermore, the suggested a posteriori approach exercises the NDS technique to maintain population diversity, a key issue in meta-heuristics, especially for multi-objective optimization. Structural mass reduction and nodal deflection maximization are two diverse objectives for the posed design problems. At the same time, stress on the components and discrete cross-sectional areas are imposed on safety and side constraints, respectively. Eight planar and spatial truss design problems demonstrate the utility of the proposed MOWSA approach for solving complex problems where the performance analysis is based on ten globally accepted metrics. Moreover, MOWSA outcomes were compared with four state-of-the-art optimization techniques to measure the viability of the suggested algorithm. MOWSA outperforms other considered algorithms concerning computational run to achieve optimal solutions and their qualitative behavior over Pareto fronts. The Matlab code for MOWSA can be obtained from https://github.com/kanak02/MOWSA.