Integral column generation for the set partitioning problem
Adil Tahir (),
Guy Desaulniers () and
Issmail El Hallaoui ()
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Adil Tahir: GERAD and Department of Mathematics and Industrial Engineering, Polytechnique Montréal
Guy Desaulniers: GERAD and Department of Mathematics and Industrial Engineering, Polytechnique Montréal
Issmail El Hallaoui: GERAD and Department of Mathematics and Industrial Engineering, Polytechnique Montréal
EURO Journal on Transportation and Logistics, 2019, vol. 8, issue 5, No 10, 713-744
Abstract:
Abstract The integral simplex using decomposition (ISUD) algorithm was recently developed to solve efficiently set partitioning problems containing a number of variables that can all be enumerated a priori. This primal algorithm generates a sequence of integer solutions with decreasing costs, leading to an optimal or near-optimal solution depending on the stopping criterion used. In this paper, we develop an integral column generation (ICG) heuristic that combines ISUD and column generation to solve set partitioning problems with a very large number of variables. Computational experiments on instances of the public transit vehicle and crew scheduling problem and of the airline crew pairing problem involving up to 2000 constraints show that ICG clearly outperforms two popular column generation heuristics (the restricted master heuristic and the diving heuristic). ICG can yield optimal or near-optimal solutions in less than 1 hour of computational time, generating up to 300 integer solutions during the solution process.
Keywords: Discrete optimization; Column generation; Integral simplex using decomposition; Crew scheduling (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)
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DOI: 10.1007/s13676-019-00145-6
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