A Multiobjective Optimization Strategy with Priority Ranking of the Design Objectives

Abstract

Generally, two types of priorities are considered among multiple objectives in the design of machine structures. One of these objectives is named the “hard objective” and is the absolutely indispensable design requirement while the other is called “soft objective” and has a lower priority order. This paper proposes a multiobjective structural optimization strategy with priority ranking of the design objectives. Further, this strategy is demonstrated on the actual example of a motorcycle frame structural design which has three design objectives: (1) an increase in static torsional rigidity, (2) a reduction of dynamic response level, and (3) a decrease in the weight of the motorcycle frame.

Optimum Structural Design Using Bio-Inspired Search Methods: A Survey and Applications

“…It is applied to a bridge structure of pre-stressed concrete. A classical optimization strategy proposed by Matsumoto et al [110], which considers a priority among the objectives to be minimized, is applied to the structural design of motorcycles considering the torsional rigidity maximization, the reduction of the level of dynamic response, and the minimization of the weight of this structure. The proposed method is based on the lexicographic approach, and the optimization is performed successively from the superposition of single-objective optimizations (multiobjective fronts are not achieved).…”

Multicriteria Optimization In Engineering: A Tutorial And Survey

“…A hierarchical approach is used by Matsumoto et al 91 in vehicle body design. They distinguish between "hard" and "soft" criteria.…”

2D decision-making for multicriteria design optimization

“…Clearly, such approach requires to decide which criteria to choose and which to drop. In (Matsumoto et al, 1993) and (Dym et al, 2002), it is shown how to develop a ranking among all criteria, and the related issue of decomposing a multiobjective design based on criteria influence is addressed in (Yoshimura et al, 2002(Yoshimura et al, , 2003. After these issues have been resolved, the reduced problem commonly takes the form shown in Figure 1.…”