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Fixed set search applied to the multi-objective minimum weighted vertex cover problem

Author

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  • Raka Jovanovic

    (Hamad bin Khalifa University)

  • Antonio P. Sanfilippo

    (Hamad bin Khalifa University)

  • Stefan Voß

    (University of Hamburg
    Pontificia Universidad Católica de Valparaíso)

Abstract

The Fixed Set Search (FSS) is a novel metaheuristic that adds a learning mechanism to the Greedy Randomized Adaptive Search Procedure (GRASP). In recent publications, its efficiency has been shown on different types of combinatorial optimization problems like routing, machine scheduling and covering. In this paper the FSS is adapted to multi-objective problems for finding Pareto Front approximations. This adaptation is illustrated for the bi-objective Minimum Weighted Vertex Cover Problem (MWVCP). In this work, a simple and effective bi-objective GRASP algorithm for the MWVCP is developed in the first stage. One important characteristic of the proposed GRASP is that it avoids the use of weighted sums of objective functions in the local search and the greedy algorithm. In the second stage, the bi-objective GRASP is extended to the FSS by adding a learning mechanism adapted to multi-objective problems. The conducted computational experiments show that the proposed FSS and GRASP algorithm significantly outperforms existing methods for the bi-objective MWVCP. To fully evaluate the learning mechanism of the FSS, it is compared to the underlying GRASP algorithm on a wide range of performance indicators related to convergence, distribution, spread and cardinality.

Suggested Citation

  • Raka Jovanovic & Antonio P. Sanfilippo & Stefan Voß, 2022. "Fixed set search applied to the multi-objective minimum weighted vertex cover problem," Journal of Heuristics, Springer, vol. 28(4), pages 481-508, August.
    • Handle: RePEc:spr:joheur:v:28:y:2022:i:4:d:10.1007_s10732-022-09499-z
    DOI: 10.1007/s10732-022-09499-z
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    References listed on IDEAS

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    1. Jovanovic, Raka & Sanfilippo, Antonio P. & Voß, Stefan, 2023. "Fixed set search applied to the clique partitioning problem," European Journal of Operational Research, Elsevier, vol. 309(1), pages 65-81.

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