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

In: Computational Intelligence and Optimization Methods for Control Engineering

Author

Listed:
  • Pierre Borne

    (Centre de recherche en informatique, signal et automatique deLille. Ecole Centrale de Lille)

  • Amira Gharbi

    (Centre de recherche en informatique, signal et automatique deLille. Ecole Centrale de Lille)

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.

Suggested Citation

  • Pierre Borne & Amira Gharbi, 2019. "Main Metaheuristics Used for the Optimization of the Control of the Complex Systems," Springer Optimization and Its Applications, in: Maude Josée Blondin & Panos M. Pardalos & Javier Sanchis Sáez (ed.), Computational Intelligence and Optimization Methods for Control Engineering, chapter 0, pages 31-49, Springer.
  • Handle: RePEc:spr:spochp:978-3-030-25446-9_2
    DOI: 10.1007/978-3-030-25446-9_2
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