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Solving parallel machine problems with delivery times and tardiness objectives

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  • Söhnke Maecker

    (WHU - Otto Beisheim School of Management)

  • Liji Shen

    (WHU - Otto Beisheim School of Management)

Abstract

This paper studies the NP-hard problem of scheduling jobs on identical parallel machines with machine-dependent delivery times to minimize the total weighted tardiness. A mixed integer linear programming formulation is presented that does not require machine-indexed variables due to a transformation of the problem. A variable neighborhood search (VNS) algorithm is proposed incorporating a local search that utilizes fast evaluation techniques (FET) to significantly improve computational efficiency of the search in four different neighborhoods. In experiments, the VNS is compared with other solution approaches on a large set of randomly generated test instances. Additionally, results for the computational benefits of our FETs are reported.

Suggested Citation

  • Söhnke Maecker & Liji Shen, 2020. "Solving parallel machine problems with delivery times and tardiness objectives," Annals of Operations Research, Springer, vol. 285(1), pages 315-334, February.
    • Handle: RePEc:spr:annopr:v:285:y:2020:i:1:d:10.1007_s10479-019-03267-2
    DOI: 10.1007/s10479-019-03267-2
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    References listed on IDEAS

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    2. Markus Hilbert & Andreas Dellnitz & Andreas Kleine, 2023. "Production planning under RTP, TOU and PPA considering a redox flow battery storage system," Annals of Operations Research, Springer, vol. 328(2), pages 1409-1436, September.

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