Yassine Yaakoubi

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Cahiers du GERAD

5 results — page 1 of 1

G-2022-31
Learning to branch for the crew pairing problem
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Crew pairing problems (CPP) are regularly solved by airlines to produce crew schedules. The goal of CPPs is to find a set of pairings (sequence of flights a...

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G-2022-03
Learning to schedule heuristics for the simultaneous stochastic optimization of mining complexes
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The simultaneous stochastic optimization of mining complexes (SSOMC) is a large-scale stochastic combinatorial optimization problem that simultaneously manag...

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G-2020-71
An improved integral column generation algorithm using machine learning for aircrew pairing
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The crew pairing problem (CPP) is solved in the first step of the crew scheduling process. It consists of creating a set of pairings (sequence of flights, co...

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G-2020-13
Machine learning in airline crew pairing to construct initial clusters for dynamic constraint aggregation
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The crew pairing problem is generally modelled as a set partitioning problem where the flights have to be partitioned in pairings. A pairing is a sequence of...

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G-2019-26
Flight-connection prediction for airline crew scheduling to construct initial clusters for OR optimizer
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We present a case study of using machine learning classification algorithms to initialize a large scale commercial operations research solver (GENCOL) in the...

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