Multicriterion Design Optimization of Complex Truss Structures Using a Novel Nature-Inspired Technique

In the real world, the design optimization of truss structures needs to optimize more than one objective function concurrently. To achieve a balanced trade-off among different design goals, a suitable optimizer is required. This study introduces a new multiobjective (MO) algorithm for the design optimization of truss structures. For this purpose, two well-known algorithms, arithmetic optimization (AOA) and whale optimization (WOA), are combined. The WOA is used initially for 50% of the iterations to move toward the global optimum Pareto front (PF) and reduce the search space. Then the AOA is used for the remaining 50% of the iterations to search locally and refine the optimum PF. The efficiency of the introduced algorithm was assessed on five truss design benchmark problems with 10, 20, 60, 72, and 120 elements, as well as a real case study involving the Burro Creek bridge. The results obtained from this algorithm were compared with those of five other well-known multiobjective algorithms based on generational distance, inverted generational distance, maximum spread, and spacing metric. The statistical results demonstrate that the approach used in this study is an effective tool for enhancing the efficiency of MO algorithms when searching for the optimal design of structures under multiple criteria.