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Enhanced arc-flow formulations to minimize weighted completion time on identical parallel machines

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  • Kramer, Arthur
  • Dell’Amico, Mauro
  • Iori, Manuel

Abstract

We consider the problem of scheduling a set of jobs on a set of identical parallel machines, with the aim of minimizing the total weighted completion time. The problem has been solved in the literature with a number of mathematical formulations, some of which require the implementation of tailored branch-and-price methods. In our work, we solve the problem instead by means of new arc-flow formulations, by first representing it on a capacitated network and then invoking a mixed integer linear model with a pseudo-polynomial number of variables and constraints. According to our computational tests, existing formulations from the literature can solve to proven optimality benchmark instances with up to 100 jobs, whereas our most performing arc-flow formulation solves all instances with up to 400 jobs and provides very low gap for larger instances with up to 1000 jobs.

Suggested Citation

  • Kramer, Arthur & Dell’Amico, Mauro & Iori, Manuel, 2019. "Enhanced arc-flow formulations to minimize weighted completion time on identical parallel machines," European Journal of Operational Research, Elsevier, vol. 275(1), pages 67-79.
    • Handle: RePEc:eee:ejores:v:275:y:2019:i:1:p:67-79
    DOI: 10.1016/j.ejor.2018.11.039
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    Cited by:

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    3. Novak, Antonin & Gnatowski, Andrzej & Sucha, Premysl, 2022. "Distributionally robust scheduling algorithms for total flow time minimization on parallel machines using norm regularizations," European Journal of Operational Research, Elsevier, vol. 302(2), pages 438-455.
    4. de Lima, Vinícius L. & Alves, Cláudio & Clautiaux, François & Iori, Manuel & Valério de Carvalho, José M., 2022. "Arc flow formulations based on dynamic programming: Theoretical foundations and applications," European Journal of Operational Research, Elsevier, vol. 296(1), pages 3-21.
    5. Alves de Queiroz, Thiago & Iori, Manuel & Kramer, Arthur & Kuo, Yong-Hong, 2023. "Dynamic scheduling of patients in emergency departments," European Journal of Operational Research, Elsevier, vol. 310(1), pages 100-116.
    6. Delorme, Maxence & Iori, Manuel & Mendes, Nilson F.M., 2021. "Solution methods for scheduling problems with sequence-dependent deterioration and maintenance events," European Journal of Operational Research, Elsevier, vol. 295(3), pages 823-837.
    7. Kramer, Arthur & Iori, Manuel & Lacomme, Philippe, 2021. "Mathematical formulations for scheduling jobs on identical parallel machines with family setup times and total weighted completion time minimization," European Journal of Operational Research, Elsevier, vol. 289(3), pages 825-840.

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