RECENT DEVELOPMENTS IN SCREENING METHODS FOR NONDOMINATED SOLUTIONS IN MULTIOBJECTIVE OPTIMIZATION

In the multiobjective problem it is not uncommon that solution methodologies produce a large number of nondominated alternatives. The decision maker is then left with the difficult task of choosing from this set. In this paper we present five methods for assisting the decision maker in this choice by reducing the set of all nondominated solutions to a manageable number. First we review three methods which have been previously published. We then present two new methods. The first builds on the earlier approaches. The second uses stochastic techniques to eliminate solutions which exhibit too much risk, leaving only a potentially small number of solutions with acceptable risk characteristics.