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Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences pp 3–18Cite as

Multi-objective Evolutionary Algorithms in Real-World Applications: Some Recent Results and Current Challenges

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Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 36))

Abstract

This chapter provides a short overview of the most significant research work that has been conducted regarding the solution of computationally expensive multi-objective optimization problems. The approaches that are briefly discussed include problem approximation, function approximation (i.e., surrogates) and evolutionary approximation (i.e., clustering and fitness inheritance). Additionally, the use of alternative approaches such as cultural algorithms, small population sizes and hybrids that use a few solutions (generated with optimizers that sacrifice diversity for the sake of a faster convergence) to reconstruct the Pareto front with powerful local search engines are also briefly discussed. In the final part of the chapter, some topics that (from the author’s perspective) deserve more research, are provided.

The author acknowledges the financial support obtained through a “Cátedra Marcos Moshinsky”.

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Notes

  1. 1.

    Without loss of generality, we will assume only minimization problems.

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  1. CINVESTAV-IPN (Evolutionary Computation Group), 07360, Mexico, D.F., Mexico

    Carlos A. Coello Coello

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  1. SIANI, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    David Greiner

  2. SIANI, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Blas Galván

  3. CIMNE, University of Jyväskylä, Jyväskylä, Finland, and Universitat Politècnica de Catalunya, Barcelona, Spain, Barcelona, Spain

    Jacques Périaux

  4. RWTH Aachen University, Aachen, Germany

    Nicolas Gauger

  5. National Technical University of Athens, Athens, Greece

    Kyriakos Giannakoglou

  6. SIANI, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Gabriel Winter

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Coello Coello, C.A. (2015). Multi-objective Evolutionary Algorithms in Real-World Applications: Some Recent Results and Current Challenges. In: Greiner, D., Galván, B., Périaux, J., Gauger, N., Giannakoglou, K., Winter, G. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-319-11541-2_1

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