Multi-Objective Evolutionary Algorithms: Past, Present, and Future

Carlos A. Coello Coello (), Silvia González Brambila (), Josué Figueroa Gamboa () and Ma. Guadalupe Castillo Tapia ()
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Carlos A. Coello Coello: CINVESTAV-IPN
Silvia González Brambila: UAM Azcapotzalco
Josué Figueroa Gamboa: UAM Azcapotzalco
Ma. Guadalupe Castillo Tapia: UAM Azcapotzalco

A chapter in Black Box Optimization, Machine Learning, and No-Free Lunch Theorems, 2021, pp 137-162 from Springer

Abstract: Abstract Evolutionary algorithms have become a popular choice for solving highly complex multi-objective optimization problems in recent years. Multi-objective evolutionary algorithms were originally proposed in the mid-1980s, but it was until the mid-1990s when they started to attract interest from researchers. Today, we have a wide variety of algorithms, and research in this area has become highly specialized. This chapter attempts to provide a general overview of multi-objective evolutionary algorithms, starting from their early origins, then moving in chronological order towards some of the most recent algorithmic developments. In the last part of the chapter, some future research paths on this topic are briefly discussed.

Date: 2021
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DOI: 10.1007/978-3-030-66515-9_5

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