CLAUTIAUX, François; HANAFI, Said; MACEDO, Rita; VOGE, Marie-Emilie; ALVES, Cláudio

doi:10.1016/j.ejor.2016.09.051

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CLAUTIAUX, François
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Institut de Mathématiques de Bordeaux [IMB]

HANAFI, Said
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]

MACEDO, Rita
Lille économie management - UMR 9221 [LEM]

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European Journal of Operational Research. 2017, vol. 258, p. 467 - 477

Elsevier

Résumé en anglais

This paper develops a general solution framework based on aggregation techniques to solve NP-Hard problems that can be formulated as a circulation model with specific side constraints. The size of the extended Mixed Integer Linear Programming formulation is generally pseudo-polynomial. To efficiently solve exactly these large scale models, we propose a new iterative aggregation and disaggregation algorithm. At each iteration, it projects the original model onto an aggregated one, producing an approximate model. The process iterates to refine the current aggregated model until the opti-mality is proved. The computational experiments on two hard optimization problems (a variant of the vehicle routing problem and the cutting-stock problem) show that a generic implementation of the proposed framework allows us to out-perform previous known methods.< Réduire

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Integer programming

Combinatorial optimization

Aggregation of integer models

Arc-flow integer models

Aggregation of integer

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Iterative aggregation and disaggregation algorithm for pseudo-polynomial network flow models with side constraints

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