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What Is Autonomous Search?

In: Hybrid Optimization

Author

Listed:
  • Youssef Hamadi

    (Microsoft Research
    LIX Ecole Polytechnique)

  • Eric Monfroy
  • Frédéric Saubion

Abstract

Autonomous search is a particular case of adaptive systems that improve their solving performance by modifying and adjusting themselves to the problem at hand, either by self-adaptation or by supervised adaptation. We propose a general definition and a taxonomy of search processes with respect to their computation characteristics. For this purpose, we decompose solvers into components and their configurations. Some computation rules between computation stages are used to formalize the solver modifications and adaptations. Using these rules, we then sketch out and classify some well known solvers and try to answer the question: “What is Autonomous Search?”

Suggested Citation

  • Youssef Hamadi & Eric Monfroy & Frédéric Saubion, 2011. "What Is Autonomous Search?," Springer Optimization and Its Applications, in: Pascal van Hentenryck & Michela Milano (ed.), Hybrid Optimization, edition 1, pages 357-391, Springer.
    • Handle: RePEc:spr:spochp:978-1-4419-1644-0_11
    DOI: 10.1007/978-1-4419-1644-0_11
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    Cited by:

    1. Mauricio Castillo & Ricardo Soto & Broderick Crawford & Carlos Castro & Rodrigo Olivares, 2021. "A Knowledge-Based Hybrid Approach on Particle Swarm Optimization Using Hidden Markov Models," Mathematics, MDPI, vol. 9(12), pages 1-21, June.
    2. Ricardo Soto & Broderick Crawford & Rodrigo Olivares & César Carrasco & Eduardo Rodriguez-Tello & Carlos Castro & Fernando Paredes & Hanns de la Fuente-Mella, 2020. "A Reactive Population Approach on the Dolphin Echolocation Algorithm for Solving Cell Manufacturing Systems," Mathematics, MDPI, vol. 8(9), pages 1-25, August.

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