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Main Metaheuristics Used for the Optimization of the Control of the Complex Systems

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Computational Intelligence and Optimization Methods for Control Engineering

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 150))

Abstract

Many optimization problems are usually NP-hard problems which prevent the implementation of exact solution methodologies. This is the reason why engineers prefer to use metaheuristics which are able to produce good solutions in a reasonable computation time. The metaheuristic approaches can be separated into two classes: the local search techniques and the global ones. Among the local search techniques, the taboo search and the simulated annealing are the most known. A possible acceleration of the convergence can be obtained by using tunneling algorithms. Concerning the global methods, the Genetic or Evolution Algorithms (GA), Ant Colony Optimization (ACO), and the Particle Swarm Optimization (PSO) are the most known.

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Authors and Affiliations

  1. Centre de recherche en informatique, signal et automatique deLille. Ecole Centrale de Lille, Cité scientifique, 48-59651, Villeneuve d’Ascq Cédex, France

    Pierre Borne & Amira Gharbi

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  1. Pierre Borne
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  2. Amira Gharbi
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Correspondence to Amira Gharbi .

Editor information

Editors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA

    Maude Josée Blondin

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  3. Institute of Automation and Industrial Computer, Polytechnic University of Valencia, Valencia, Spain

    Javier Sanchis Sáez

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Borne, P., Gharbi, A. (2019). Main Metaheuristics Used for the Optimization of the Control of the Complex Systems. In: Blondin, M., Pardalos, P., Sanchis Sáez, J. (eds) Computational Intelligence and Optimization Methods for Control Engineering. Springer Optimization and Its Applications, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-030-25446-9_2

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