<strong>A brief review of multi-objective optimization proposals that interactively incorporate preferences.</strong>

Abstract

The problems in which there is a conflict between objectives, naturally occur in the real world, in which also intervenes the presence of a decision maker. The multi-objective problem solution has been approached through many multi-objective optimization algorithms. There are available many algorithms for solving these types of problems, mostly for two or three objectives problems, but in the real world, the number of conflicting objectives is large-scale. These algorithms provide many solutions to the decision-maker but, even though all of these are good and efficient solutions under the Pareto dominance paradigm (efficient solutions known as non-dominated), this does not solve the problem completely, because, this large number of solutions found, could overwhelm the DM at the time of selecting the one he considers best for him. There is an emerging area in multi-objective optimization, in which decision-makers preferences are incorporated, but these can be done at different times in the optimization process: a priori, a posteriori and interactively.