Construct, merge, solve and adapt

Christian Blum ()
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Christian Blum: Campus UAB

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2025, vol. 33, issue 2, No 7, 357-377

Abstract: Abstract The CMSA algorithm for combinatorial optimization is a hybrid technique based on repeatedly solving sub-instances to the original problem instance. The incumbent sub-instance is extended at each iteration by the probabilistic generation of valid solutions to the original problem instance and by adding the components found in these solutions to the sub-instance. In addition, the incumbent sub-instance is reduced at each iteration by removing seemingly useless solution components. In recent years the usefulness of the CMSA algorithm has been shown by a range of applications to different combinatorial optimization problems. In this work, we provide a gentle introduction to CMSA by describing the application to the so-called minimum global domination problem as an example.

Keywords: Combinatorial optimization; Metaheuristics; Hybrid algorithms; Global domination; CMSA; 90-05; 90-08; 68T20; 68U01; 68R01 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11750-024-00689-5

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