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Intensification, learning and diversification in a hybrid metaheuristic: an efficient unification

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  • Vinícius R. Máximo

    (Universidade Federal de São Paulo (UNIFESP))

  • Mariá C. V. Nascimento

    (Universidade Federal de São Paulo (UNIFESP))

Abstract

Hybrid heuristic methods have lately been pointed out as an efficient approach to combinatorial optimization problems. The main reason behind this is that, by combining components from different metaheuristics, it is possible to explore solutions (which would be unreachable without hybridization) in the search space. In particular, evolutionary algorithms may get trapped into local optimum solutions due to the insufficient diversity of the solutions influencing the search process. This paper presents a hybridization of the recently proposed metaheuristic—intelligent-guided adaptive search (IGAS)—with the well-known path-relinking algorithm to solve large scale instances of the maximum covering location problem. Moreover, it proposes a slight change in IGAS that was tested through computational experiments and has shown improvement in its computational cost. Computational experiments also attested that the hybridized IGAS outperforms the results found in the literature.

Suggested Citation

  • Vinícius R. Máximo & Mariá C. V. Nascimento, 2019. "Intensification, learning and diversification in a hybrid metaheuristic: an efficient unification," Journal of Heuristics, Springer, vol. 25(4), pages 539-564, October.
    • Handle: RePEc:spr:joheur:v:25:y:2019:i:4:d:10.1007_s10732-018-9373-1
    DOI: 10.1007/s10732-018-9373-1
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    References listed on IDEAS

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    1. Galvao, Roberto D. & Gonzalo Acosta Espejo, Luis & Boffey, Brian, 2000. "A comparison of Lagrangean and surrogate relaxations for the maximal covering location problem," European Journal of Operational Research, Elsevier, vol. 124(2), pages 377-389, July.
    2. Resende, Mauricio G.C. & Werneck, Renato F., 2006. "A hybrid multistart heuristic for the uncapacitated facility location problem," European Journal of Operational Research, Elsevier, vol. 174(1), pages 54-68, October.
    3. Galvao, Roberto Dieguez & ReVelle, Charles, 1996. "A Lagrangean heuristic for the maximal covering location problem," European Journal of Operational Research, Elsevier, vol. 88(1), pages 114-123, January.
    4. Richard Church & Charles R. Velle, 1974. "The Maximal Covering Location Problem," Papers in Regional Science, Wiley Blackwell, vol. 32(1), pages 101-118, January.
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    Cited by:

    1. Emanuel Vega & Ricardo Soto & Broderick Crawford & Javier Peña & Carlos Castro, 2021. "A Learning-Based Hybrid Framework for Dynamic Balancing of Exploration-Exploitation: Combining Regression Analysis and Metaheuristics," Mathematics, MDPI, vol. 9(16), pages 1-23, August.

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