Multi-Criteria Decision-Making: The Intersection of Search, Preference Tradeoff, and Interaction Visualization Processes

Abstract

Summary form only given. The goal of the First IEEE Symposium of Computational Intelligence in Multicriteria Decision Making (MCDM 2007) is to provide a common forum for three scientific communities that have addressed different aspects of the MCDM problem and provided complementary approaches to its solution. The first approach is the search process over the space of possible solutions. We must perform efficient searches in multi- (or sometimes many-) dimensional spaces to identify the non-dominated solutions that compose the Pareto set. This search is driven by the solution evaluations, which might be probabilistic, stochastic, or imprecise, rather than deterministic. The second approach is the preference tradeoff process. We need to elicit, represent, evaluate, and aggregate the decision-maker's preferences to select a single solution (or a small subset of solutions) from the Pareto set. These preferences may be ill defined, and state or time-dependent rather than constant values. The aggregation mechanism may be as simple as a linear combination or as complex as a knowledge-driven model. The third approach is the interactive visualization process, which enables progressive decisions. We often want to embed the decision-maker in the solution refinement and selection loop. To this end, we need to show the impacts that intermediate tradeoffs in one sub-space could have in the other ones, while allowing him/her to retract or modify any intermediate steps to strike appropriate tradeoff balances. Given this perspective, we believe that MCDM resides in the intersections of these approaches