This chapter provides a short overview of multi-objective optimization using metaheuristics. The chapter includes a description of some of the main metaheuristics that have been used for multi-objective optimization. Although special emphasis is made on evolutionary algorithms, other metaheuristics, such as particle swarm optimization, artificial immune systems, and ant colony optimization, are also briefly discussed. Other topics such as applications and recent algorithmic trends are also included. Finally, some of the main research trends that are worth exploring in this area are briefly discussed.
CITATION STYLE
Coello, C. A. C. (2018). Multi-objective Optimization. In Handbook of Heuristics (pp. 1–28). Springer International Publishing. https://doi.org/10.1007/978-3-319-07153-4_17-1
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