MORIME: A multi-objective RIME optimization framework for efficient truss design

Abstract

Multi objective optimization (MOO) is very important in structural engineering, especially in truss design where a trade off between weight reduction and compliance is needed to maximize the efficiency. Usually, conventional optimization algorithms have difficulty in solving complex MOO tasks, and in generating diverse, high quality solutions for various structural configurations. To overcome these challenges, this study proposes a Multi Objective RIME (MORIME) algorithm that uses improved non-dominated sorting and crowding distance techniques to optimize weight and compliance over eight truss designs. With respect to Hypervolume (HV), Inverted Generational Distance (IGD), and Spacing (SP) metrics, it performed better than other established methods such as NSGA-II, MOEA/D, MOMVO, MOTEO, MOLCA, and MORIME, leading to better convergence and diversity of solution sets. The results show that MORIME is a good tool for dealing with complex multi objective optimization landscapes and that it is better than biologically inspired and hybrid optimization methods. MORIME is a powerful tool for structural engineers to produce well balanced truss designs, which meet stringent weight and compliance requirements in a multiobjective setting. MORIME is one attractive feature because it can generate optimal and diverse solutions in truss optimization, resulting in high quality design results.

Keywords

• Structural engineering
• Pareto optimality
• Compliance reduction
• Multiobjective optimization