Refined ranking relations for multi objective optimization andapplication to P-ACO

Abstract

Two new ranking methods for solutions of multi objective optimization problems are proposed in this paper. Theoretical results show that both new ranking methods form a total preorder and are refinements of the pareto dominance relation. These properties make the ranking methods suitable for the selection of a subset of good solutions from a set of non-dominated solutions as needed by meta-heuristics. In particular, this is shown experimentally for a Populationbased ACO that uses the ranking methods to solve a multi objective flow shop problem.