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Hybrid scatter tabu search for unconstrained global optimization

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  • Abraham Duarte
  • Rafael Martí
  • Fred Glover
  • Francisco Gortazar

Abstract

The problem of finding a global optimum of an unconstrained multimodal function has been the subject of intensive study in recent years, giving rise to valuable advances in solution methods. We examine this problem within the framework of adaptive memory programming (AMP), focusing particularly on AMP strategies that derive from an integration of Scatter Search and Tabu Search. Computational comparisons involving 16 leading methods for multimodal function optimization, performed on a testbed of 64 problems widely used to calibrate the performance of such methods, disclose that our new Scatter Tabu Search (STS) procedure is competitive with the state-of-the-art methods in terms of the average optimality gap achieved. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Abraham Duarte & Rafael Martí & Fred Glover & Francisco Gortazar, 2011. "Hybrid scatter tabu search for unconstrained global optimization," Annals of Operations Research, Springer, vol. 183(1), pages 95-123, March.
    • Handle: RePEc:spr:annopr:v:183:y:2011:i:1:p:95-123:10.1007/s10479-009-0596-2
    DOI: 10.1007/s10479-009-0596-2
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    References listed on IDEAS

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    1. Hedar, Abdel-Rahman & Fukushima, Masao, 2006. "Tabu Search directed by direct search methods for nonlinear global optimization," European Journal of Operational Research, Elsevier, vol. 170(2), pages 329-349, April.
    2. Chelouah, Rachid & Siarry, Patrick, 2005. "A hybrid method combining continuous tabu search and Nelder-Mead simplex algorithms for the global optimization of multiminima functions," European Journal of Operational Research, Elsevier, vol. 161(3), pages 636-654, March.
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    Cited by:

    1. Javier Cano & Cesar Alfaro & Javier Gomez & Abraham Duarte, 2022. "Out of the Niche: Using Direct Search Methods to Find Multiple Global Optima," Mathematics, MDPI, vol. 10(9), pages 1-20, April.
    2. Andrei Panteleev & Maria Karane, 2023. "Application of a Novel Multi-Agent Optimization Algorithm Based on PID Controllers in Stochastic Control Problems," Mathematics, MDPI, vol. 11(13), pages 1-21, June.

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