FROGER, Aurélien; SADYKOV, Ruslan

doi:10.1016/j.ejor.2022.07.012

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FROGER, Aurélien
Institut de Mathématiques de Bordeaux [IMB]
Formulations étendues et méthodes de décomposition pour des problèmes génériques d'optimisation [EDGE]

SADYKOV, Ruslan
Formulations étendues et méthodes de décomposition pour des problèmes génériques d'optimisation [EDGE]

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European Journal of Operational Research. 2022

Elsevier

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2022

Résumé en anglais

We study the prize-collecting job sequencing problem with one common and multiple secondary resources. In this problem, a set of jobs is given, each with a profit, multiple time windows for its execution, and a duration during which it requires the main resource. Each job also requires a preassigned secondary resource before, during, and after its use of the main resource. The goal is to select and schedule the subset of jobs that maximize the total profit. We present a new mixed integer linear programming formulation of the problem and a branch-cut-and-price algorithm as an exact solution method. We also introduce a heuristic algorithm to tackle larger instances. Extensive numerical experiments show that our exact algorithm can solve to optimality literature instances with up to 500 jobs for a particular dataset and up to 250 jobs for another dataset with different characteristics. Our heuristic builds high-quality solutions in a small computational time. It computes new best-known solutions for most of the larger instances.< Réduire

Mots clés en anglais

Iterated local search

Branch-cut-and-price

Labeling algorithm

Sequencing

Scheduling

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New exact and heuristic algorithms to solve the prize-collecting job sequencing problem with one common and multiple secondary resources

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Résumé en anglais

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