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A simple and effective algorithm for the maximum happy vertices problem

Author

Listed:
  • Marco Ghirardi

    (DIGEP, Politecnico di Torino)

  • Fabio Salassa

    (DIGEP, Politecnico di Torino)

Abstract

In a recent paper, a solution approach to the Maximum Happy Vertices Problem has been proposed. The approach is based on a constructive heuristic improved by a matheuristic local search phase. We propose a new procedure able to outperform the previous solution algorithm both in terms of solution quality and computational time. Our approach is based on simple ingredients implying as starting solution generator an approximation algorithm and as an improving phase a new matheuristic local search. The procedure is then extended to a multi-start configuration, able to further improve the solution quality at the cost of an acceptable increase in computational time.

Suggested Citation

  • Marco Ghirardi & Fabio Salassa, 2022. "A simple and effective algorithm for the maximum happy vertices problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 181-193, April.
    • Handle: RePEc:spr:topjnl:v:30:y:2022:i:1:d:10.1007_s11750-021-00610-4
    DOI: 10.1007/s11750-021-00610-4
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    References listed on IDEAS

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    1. Martinez-Sykora, A. & Alvarez-Valdes, R. & Bennell, J.A. & Ruiz, R. & Tamarit, J.M., 2017. "Matheuristics for the irregular bin packing problem with free rotations," European Journal of Operational Research, Elsevier, vol. 258(2), pages 440-455.
    2. Federico Della Croce & Fabio Salassa, 2014. "A variable neighborhood search based matheuristic for nurse rostering problems," Annals of Operations Research, Springer, vol. 218(1), pages 185-199, July.
    3. Shahmanzari, Masoud & Aksen, Deniz & Salhi, Saïd, 2020. "Formulation and a two-phase matheuristic for the roaming salesman problem: Application to election logistics," European Journal of Operational Research, Elsevier, vol. 280(2), pages 656-670.
    4. Macrina, Giusy & Laporte, Gilbert & Guerriero, Francesca & Di Puglia Pugliese, Luigi, 2019. "An energy-efficient green-vehicle routing problem with mixed vehicle fleet, partial battery recharging and time windows," European Journal of Operational Research, Elsevier, vol. 276(3), pages 971-982.
    5. Fanjul-Peyro, Luis & Perea, Federico & Ruiz, Rubén, 2017. "Models and matheuristics for the unrelated parallel machine scheduling problem with additional resources," European Journal of Operational Research, Elsevier, vol. 260(2), pages 482-493.
    6. Billaut, Jean-Charles & Della Croce, Federico & Grosso, Andrea, 2015. "A single machine scheduling problem with two-dimensional vector packing constraints," European Journal of Operational Research, Elsevier, vol. 243(1), pages 75-81.
    7. Federico Della Croce & Andrea Grosso & Fabio Salassa, 2014. "A matheuristic approach for the two-machine total completion time flow shop problem," Annals of Operations Research, Springer, vol. 213(1), pages 67-78, February.
    8. Doi, Tsubasa & Nishi, Tatsushi & Voß, Stefan, 2018. "Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time," European Journal of Operational Research, Elsevier, vol. 267(2), pages 428-438.
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