Multi-objective Variants of Water Strider Algorithm for Construction Engineering Optimization Problems

Authors

  • Ali Kaveh
    Affiliation
    School of Civil Engineering, Iran University of Science and Technology, P.O. Box 16846-13114, Narmak, Tehran, Iran
  • Ali Akbar Shirzadi Javid
    Affiliation
    School of Civil Engineering, Iran University of Science and Technology, P.O. Box 16846-13114, Narmak, Tehran, Iran
  • Yasin Vazirinia
    Affiliation
    School of Civil Engineering, Iran University of Science and Technology, P.O. Box 16846-13114, Narmak, Tehran, Iran
https://doi.org/10.3311/PPci.40442

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.

Keywords:

construction site layout planning, water strider algorithm, non-dominated sorting, grid-based multi objective, truss structures, project scheduling

Citation data from Crossref and Scopus

Published Online

2025-07-02

How to Cite

Kaveh, A., Shirzadi Javid, A. A., Vazirinia, Y. “Multi-objective Variants of Water Strider Algorithm for Construction Engineering Optimization Problems”, Periodica Polytechnica Civil Engineering, 2025. https://doi.org/10.3311/PPci.40442

Issue

Section

Research Article