Multi-objective Optimization

Living reference work entry

Abstract

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.

Keywords

Multi-objective optimization metaheuristics evolutionary algorithms optimization 

Notes

Acknowledgements

The author acknowledges support from CONACYT project no. 221551.

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© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Departmento de ComputaciónCINVESTAV-IPNMéxico D.F.México

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