Improved integer linear programming formulations for the job Sequencing and tool Switching Problem

Daniele Catanzaro 1 Martine Labbé 2, 3 Luis Gouveia 4
2 INOCS - Integrated Optimization with Complex Structure
ULB - Université Libre de Bruxelles [Bruxelles], Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : In this article we investigate the job Sequencing and tool Switching Problem (SSP), a NPNP-hard combinatorial optimization problem arising from computer and manufacturing systems. Starting from the results described in Tang and Denardo (1987), Crama et al. (1994) and Laporte et al. (2004), we develop new integer linear programming formulations for the problem that are provably better than the alternative ones currently described in the literature. Computational experiments show that the lower bounds obtained by the linear relaxation of the considered formulations improve, on average, upon those currently described in the literature and suggest, at the same time, new directions for the development of future exact solution approaches.
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https://hal.archives-ouvertes.fr/hal-01255516
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Submitted on : Wednesday, January 13, 2016 - 6:27:12 PM
Last modification on : Friday, July 26, 2019 - 11:58:03 AM

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Daniele Catanzaro, Martine Labbé, Luis Gouveia. Improved integer linear programming formulations for the job Sequencing and tool Switching Problem. European Journal of Operational Research, Elsevier, 2015, 244 (3), pp.766-777. ⟨10.1016/j.ejor.2015.02.018⟩. ⟨hal-01255516⟩

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