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Metaheuristic Algorithms

In: The Quadratic Unconstrained Binary Optimization Problem

Author

Listed:
  • Yang Wang

    (Northwestern Polytechnical University)

  • Jin-Kao Hao

    (Universitë d’Angers)

Abstract

Metaheuristic algorithms are practically used to produce approximate solutions to large QUBO instances that cannot be solved exactly due to the high computational complexity. This chapter is dedicated to a review on the general metaheuristic approach for solving the QUBO. First, we present some basic components of local search that are widely used in the design of state-of-the-art metaheuristic algorithms for the problem. Then we overview the metaheuristic algorithms in the literature by groups of fast solving heuristics, local search based methods and population based search methods. Finally, we review some of the most popular and effective metaheuristic algorithms and present experimental results on different sets of instances.

Suggested Citation

  • Yang Wang & Jin-Kao Hao, 2022. "Metaheuristic Algorithms," Springer Books, in: Abraham P. Punnen (ed.), The Quadratic Unconstrained Binary Optimization Problem, chapter 0, pages 241-259, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-04520-2_9
    DOI: 10.1007/978-3-031-04520-2_9
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