Preference modeling and model management for interactive multi-objective evolutionary optimization

Abstract

Multiobjective optimization and decision making are strongly inter-related. This paper presents an interactive approach for the integration of expert preferences into multi-objective evolutionary optimization. The experts underlying preference is modeled only based on comparative queries that are designed to distinguish among the non-dominant solutions with minimal burden on the decision maker. The preference based approach constitutes a compromise between global approximation of a Pareto front and aggregation of objectives into a scalar utility function. The model captures relevant aspects of multi-objective decision making, such as preference handling, ambiguity and incommensurability. The efficiency of the approach in terms of number of expert decisions and convergence to the optimal solution are analyzed on the basis of an artificial decision behavior with respect to optimization benchmarks. © 2010 Springer-Verlag Berlin Heidelberg.