A survey of multiobjective optimization in engineering design

Real world engineering design problems are usually characterized by the presence of many conflicting objectives. Therefore, it is natural to look at the engineering design problem as a multiobjective optimization problem. This report summarizes a survey of techniques to conduct multiobjective optimization in an engineering design context. The report starts with discussing some of the difficulties of expressing the value of a deign and how to characterize different design variables. Thereafter we look more closely on the design problem in order to reformulate the design problem as a multiobjective optimization problem. As engineering design problems often consist of a mixture of numerical simulations, analytical calculations and catalog selections, there is no easy way of calculating derivatives of the objectives function. Therefore, non-gradient optimization methods are better suited for these types of problems. Different types of non-gradient method are discussed in the report and different ways of developing hybrid methods are presented as well. As most optimization problems are multiobjective to there nature, there are many methods available to tackle these kind of problems. Generally, a multiobjective optimization problem can be handled in four different ways depending on when the decision-maker articulates his or her preference on the different objectives; never, before, during or after the actual optimization procedure. The most common way is to aggregate the different objectives to one figure of merit by using a weighted sum and the conduct the actual optimization. There is however an abundance of other ways in which multiobjective optimization can be conducted, some of them are presented in this report. A survey of multiobjective optimization methods in engineering design