Simulation study demonstrates enhanced weight and compliance minimization across truss structures, indicating superior performance for constrained engineering design.
This study introduces Multi-Objective Chaos Game Optimization (MOCGO), a metaheuristic algorithm developed for the purpose of handling multi-objective structural optimization problems with constraints. In doing so, MOCGO utilizes a single-objective algorithm known as Chaos Game Optimization (CGO) in conjunction with chaos exploration dynamics, a diversity-preserving archive, and a grid-selection process to create an effective set of Pareto optimal solutions. This algorithm has been tested on six different trusses (10-bar to 120-bar) based on the problem of minimizing the weight and compliance of a structure while satisfying the stress constraint criteria. As measures of fitness, MOCGO performs significantly better than other algorithms, including NSGA-II, MOGOA, MOALO, and MOAVOA. These results demonstrate MOCGO as an efficient and robust approach for constrained multi-objective structural design.
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Pipalia et al. (2026) studied this question.
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