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Article Dans Une Revue SIAM Journal on Optimization Année : 2020

STRONG CONVEX NONLINEAR RELAXATIONS OF THE POOLING PROBLEM

James Luedtke
  • Fonction : Auteur
Jeff Linderoth
  • Fonction : Auteur
Jonas Schweiger
  • Fonction : Auteur

Résumé

We investigate new convex relaxations for the pooling problem, a classic nonconvex production planning problem in which input materials are mixed in intermediate pools, with the outputs of these pools further mixed to make output products meeting given attribute percentage requirements. Our relaxations are derived by considering a set which arises from the formulation by considering a single product, a single attribute, and a single pool. The convex hull of the resulting nonconvex set is not polyhedral. We derive valid linear and convex nonlinear inequalities for the convex hull, and demonstrate that different subsets of these inequalities define the convex hull of the nonconvex set in three cases determined by the parameters of the set. Computational results on literature instances and newly created larger test instances demonstrate that the inequalities can significantly strengthen the convex relaxation of the pq-formulation of the pooling problem, which is the relaxation known to have the strongest bound.
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Dates et versions

hal-03008697 , version 1 (16-11-2020)

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  • HAL Id : hal-03008697 , version 1

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James Luedtke, Claudia d'Ambrosio, Jeff Linderoth, Jonas Schweiger. STRONG CONVEX NONLINEAR RELAXATIONS OF THE POOLING PROBLEM. SIAM Journal on Optimization, 2020. ⟨hal-03008697⟩
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