Many‑objective meta-heuristic methods for solving constrained truss optimisation problems: A comparative analysis

• Published in: MethodsX 2023-01, Vol.10, p.102181-102181, Article 102181
• Main Authors: Panagant, Natee, Kumar, Sumit, Tejani, Ghanshyam G., Pholdee, Nantiwat, Bureerat, Sujin
• Format: Article
• Language: English
• Subjects: Buckling; Computer Science; Constraint optimization; Evolutionary methods; Many‑objective meta-heuristic methods; Natural frequency; Structural design
• ISSN: 2215-0161; 2215-0161
• DOI: 10.1016/j.mex.2023.102181

Many-objective truss structure problems from small to large-scale problems with low to high design variables are investigated in this study. Mass, compliance, first natural frequency, and buckling factor are assigned as objective functions. Since there are limited optimization methods that have been developed for solving many-objective truss optimization issues, it is important to assess modern algorithms performance on these issues to develop more effective techniques in the future. Therefore, this study contributes by investigating the comparative performance of eighteen well-established algorithms, in various dimensions, using four metrics for solving challenging truss problems with many objectives. The statistical analysis is performed based on the objective function best mean and standard deviation outcomes, and Friedman's rank test. MMIPDE is the best algorithm as per the overall comparison, while SHAMODE with whale optimisation approach and SHAMODE are the runners-up.•A comparative test to measure the efficiency of eighteen state-of-the-practice methods is performed.•Small to large-scale truss design challenges are proposed for the validation.•The performance is measured using four metrics and Friedman's rank test. [Display omitted]