Solution methods for multiple objective decision models
Thesis DisciplineOperations Research
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
This thesis is concerned with an investigation of solution methods for continuous multiple objective decision models (MODM's). A number of different solution methods which have appeared in the literature are reviewed with an emphasis on the underlying concepts of the methods. The following chapter examines the solution of MODM’S from the other side, namely the behavioural aspects of decision making. Having gained an appreciation of exactly how people do make decisions I the intent of the thesis is twofold. Firstly, to develop new solution methods which can accommodate the decision maker (DM) in whatever his or her particular decision strategy is. And secondly, it is to empirically examine four solution methods with respect to users' preferences among them. Of these four solution methods, three are among the most well known in the literature and all can cite practical application. Two new solution methods have been developed. Both of these methods are based on a specific formulation of the MODM which is known as the maxmin formulation. The theory of the maxmin formulation is developed in Chapter 4. By using the Lagrange multipliers at the optimal solution, suitable pairwise tradeoff information can be presented to the DM. This forms the basis for the first solution method, which interacts with the DM as he or she progressively provides preference information. The other solution method makes use of a branch of Psychology called Social Judgement Theory and incorporates this into the solution method. This second method is especially applicable to the multiple DM situation. In the empirical examination of solution methods it was found that one solution method was clearly preferred over the other three. The thesis concludes with a discussion of approaches for reducing the number of objectives in a MODM.