A Tutorial on Multi-Objective Optimization using Metaheuristics


This paper provides an overview of the use of metaheuristics for solving multi-objective optimization problems. The metaheuristics discussed include multi-objective evolutionary algorithms (going from the early approches to the most recent research trends in that area), multi-objective particle swarm optimizers, multi-objective artificial immune systems, multi-objective ant colony systems and multi-objective scatter search. In the final part of the paper, we provide a review of sample applications of multi-objective metaheuristics, and a discussion of some of the topics in which more research is required.