Refined ranking relations for selection of solutions in multi objective metaheuristics
Ranking methods for solutions of multi objective optimization problems are proposed. Both methods are refinements of the Pareto dominance relation. The methods help metaheuristics to select good solutions. Desirable properties for applications are shown theoretically. We report experimental results for PACO and GA for multi objective flow shop problem.
ranking relations multi objective optimization ant colony optimization genetic algorithms flow shop scheduling problem