A multiobjective discrete combination optimization method for dynamics design of engineering structures

This paper presents a new multiobjective discrete optimization method for the engineering design of dynamic problems. A discrete combinatorial optimization problem is solved using a particle swarm optimization algorithm coupled with a stair-form interpolation model. To address multiobjective optimization issues, a weighted average approach is implemented to convert the multiobjective optimization problem into an equivalent single-objective optimization problem. Design constraints are taken into consideration by using the penalty function strategy. The proposed method is first verified with a 10-bar truss structure design problem, where the cross-sectional area of each bar is optimized to minimize both volume and node displacement. Second, the dynamic issue for hybrid composite laminates is investigated by maximizing the fundamental frequency and minimizing the cost. The results reveal that the optimized results generated by the proposed method agree well with those from other approaches.