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Formulation Space Search Metaheuristic

In: The Palgrave Handbook of Operations Research

Author

Listed:
  • Nenad Mladenović

    (Khalifa University)

  • Jack Brimberg

    (Royal Military College of Canada)

  • Dragan Urošević

    (Mathematical Institute of the Serbian Academy of Sciences and Arts)

Abstract

Many methods for solving discrete and continuous global optimization problems are based on changing one formulation to another, which is either equivalent or very close to it. These types of methods include dual, primal-dual, Lagrangian, linearization, surrogation, convexification methods, coordinate system change, discrete/continuous reformulations, to mention a few. However, in all those classes, the set of formulations of one problem are not considered as a set having some structure provided with some order relation among formulations. The main idea of Formulation Space Search (FSS) is to provide the set of formulations with some metric or quasi-metric relations, used for solving a given class or type of problem. In that way, the (quasi) distance between formulations is introduced, and the search space is extended to the set of formulations as well. This chapter presents the general methodology of FSS, and gives an overview of several applications taken from the literature that fall within this framework. We also examine a few of these applications in more detail.

Suggested Citation

  • Nenad Mladenović & Jack Brimberg & Dragan Urošević, 2022. "Formulation Space Search Metaheuristic," Springer Books, in: Saïd Salhi & John Boylan (ed.), The Palgrave Handbook of Operations Research, chapter 0, pages 405-445, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-96935-6_12
    DOI: 10.1007/978-3-030-96935-6_12
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