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Communication Dans Un Congrès Année : 2017

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

Résumé

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.
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Dates et versions

hal-03384513 , version 1 (19-10-2021)

Identifiants

  • HAL Id : hal-03384513 , version 1

Citer

François Clautiaux, Said Hanafi, Rita Macedo, Marie-Emilie Voge, Cláudio Alves. Iterative aggregation and disaggregation algorithm for pseudo-polynomial network flow models with side constraints. ISCO 2016, International Symposium on Combinatorial Optimization, May 2016, Vietri sul Mare, Italy. pp.467-477. ⟨hal-03384513⟩
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