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The effectiveness of the longest delivery time rule for the flow shop delivery time problem

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  • Philip Kaminsky

Abstract

In the flow shop delivery time problem, a set of jobs has to be processed on m machines. Every machine has to process each one of the jobs, and every job has the same routing through the machines. The objective is to determine a sequence of the jobs on the machines so as to minimize maximum delivery completion time over all the jobs, where the delivery completion time of a job is the sum of its completion time, and the delivery time associated with that job. In this paper, we prove the asymptotic optimality of the Longest Delivery Time algorithm for the static version of this problem, and the Longest Delivery Time among Available Jobs (LDTA) algorithm for the dynamic version of this problem. In addition, we present the result of computational testing of the effectiveness of these algorithms. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003

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  • Philip Kaminsky, 2003. "The effectiveness of the longest delivery time rule for the flow shop delivery time problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(3), pages 257-272, April.
    • Handle: RePEc:wly:navres:v:50:y:2003:i:3:p:257-272
    DOI: 10.1002/nav.10054
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    References listed on IDEAS

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    1. Carlier, Jacques, 1982. "The one-machine sequencing problem," European Journal of Operational Research, Elsevier, vol. 11(1), pages 42-47, September.
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    Cited by:

    1. Liang-Liang Fu & Mohamed Ali Aloulou & Christian Artigues, 2018. "Integrated production and outbound distribution scheduling problems with job release dates and deadlines," Journal of Scheduling, Springer, vol. 21(4), pages 443-460, August.
    2. Philip Kaminsky & Onur Kaya, 2008. "Scheduling and due‐date quotation in a make‐to‐order supply chain," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(5), pages 444-458, August.
    3. Zhi-Long Chen, 2010. "Integrated Production and Outbound Distribution Scheduling: Review and Extensions," Operations Research, INFORMS, vol. 58(1), pages 130-148, February.

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