Using multi-objective evolutionary algorithms for single-objective optimization |
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Authors: | Carlos Segura Carlos A Coello Coello Gara Miranda Coromoto León |
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Institution: | 1. Dpto. de Computación, UMI LAFMIA 3175 CNRS at CINVESTAV-IPN, Mexico, D.F., Mexico 2. Dpto. de Computación (Evolutionary Computation Group), CINVESTAV-IPN, Mexico, D.F., Mexico 3. Dpto. Estadística, I. O. y Computación, Universidad de La Laguna, Tenerife, Spain
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Abstract: | In recent decades, several multi-objective evolutionary algorithms have been successfully applied to a wide variety of multi-objective optimization problems. Along the way, several new concepts, paradigms and methods have emerged. Additionally, some authors have claimed that the application of multi-objective approaches might be useful even in single-objective optimization. Thus, several guidelines for solving single-objective optimization problems using multi-objective methods have been proposed. This paper offers a survey of the main methods that allow the use of multi-objective schemes for single-objective optimization. In addition, several open topics and some possible paths of future work in this area are identified. |
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