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Core-guided method for constraint-based multi-objective combinatorial optimization

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Abstract

Multi-Objective Combinatorial Optimization(MOCO), which consists of several conflicting objectives to be optimized, finds an ever-increasing number of uses in many real-world applications. In past years, the research of MOCO mainly focuses on evolutionary algorithms. Recently, constraint-based methods come into the view and have been proved to be effective on MOCO problems. This paper builds on the previous works of constraint-based algorithm MCSEnumPD(AAAI-18) using path diversification method. Due to the inadequacy that the original method fails to prune the redundant search space effectively, this paper proposes the definition of infeasible path and develops a novel algorithm that exploits the properties of unsatisfiable cores, referred as CgPDMCS. The approach extends MCSEnumPD algorithm with a core-guided path diversification method, which avoids solving infeasible paths representing the supersets of the unsatisfiable cores. Experimental results show that the novel approach provides further performance gains over the previous constraint-based algorithms, especially for the instances tightly constrained.

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Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Naiyu Tian, Dantong Ouyang, Yimou Hou & Liming Zhang

  2. School of Computer Science and Information Technology, Northeast Normal University, Changchun, 130012, China

    Yiyuan Wang

  3. Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun, 130012, China

    Naiyu Tian, Dantong Ouyang, Yiyuan Wang, Yimou Hou & Liming Zhang

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  1. Naiyu Tian
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  2. Dantong Ouyang
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  5. Liming Zhang
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Correspondence to Liming Zhang.

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This work is supported by the National Natural Science Foundation of China (Grant Nos. 61672261, 61872159,61806050, 61972063) and Fundamental Research Funds for the Central Universities 2412020FZ030, Jilin Education Department JJKH20190289KJ.

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Tian, N., Ouyang, D., Wang, Y. et al. Core-guided method for constraint-based multi-objective combinatorial optimization. Appl Intell 51, 3865–3879 (2021). https://doi.org/10.1007/s10489-020-01998-5

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