Unveiling innovative design principles by means of multiple conflicting objectives

Optimization principles are often used in engineering design activities for nding solutions which can not be bettered. The use of a single objective for design usually results in only one optimum solution, whereas the consideration of multiple conicting objectives results in a number of trade-off Pareto-optimal solutions. Investigating the Pareto-optimal solutions for any similarity or relationship among their design variables may provide vital design principles, which may not be possible to get by any other means. In this paper, we illustrate the concept of optimization in the presence of multiple conflicting objectives and then present one multiobjective optimization algorithm based on evolutionary algorithms. Thereafter, a number of engineering design optimization case studies are presented to first find a set of Pareto-optimal solutions and then analyze them to unveil important design principles which would be of great importance to a designer. The breadth of case studies considered in this paper and the demonstrated discovery of useful design principles should encourage the study of multiobjective evolutionary optimization and motivate researchers and practitioners to perform similar studies involving other engineering design problems.