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Probabilistic Analysis and Practical Algorithms for the Flow Shop Weighted Completion Time Problem

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  • Philip Kaminsky

    (University of California, Berkeley, California)

  • David Simchi-Levi

    (Northwestern University, Chicago, Illinois)

Abstract

In the flow shop weighted completion 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 the sum of the weighted completion times of all jobs on the final machine. In this paper, we present a characterization of the asymptotic optimal solution value for general distributions of the job processing times and weights. In particular, we show that the optimal objective value of this problem is asymptotically equivalent to certain single and parallel machine scheduling problems. This characterization leads to a better understanding of the effectiveness of the celebrated weighted shortest processing time algorithm, as well as to the development of an effective algorithm closely related to the profile fitting heuristic, which was previously utilized for flow shop makespan problems. Computational results show the effectiveness of WSPT and this modified profile fitting heuristic on a set of random test problems.

Suggested Citation

  • Philip Kaminsky & David Simchi-Levi, 1998. "Probabilistic Analysis and Practical Algorithms for the Flow Shop Weighted Completion Time Problem," Operations Research, INFORMS, vol. 46(6), pages 872-882, December.
    • Handle: RePEc:inm:oropre:v:46:y:1998:i:6:p:872-882
    DOI: 10.1287/opre.46.6.872
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    References listed on IDEAS

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    1. Julien Bramel & David Simchi-Levi, 1995. "A Location Based Heuristic for General Routing Problems," Operations Research, INFORMS, vol. 43(4), pages 649-660, August.
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    Cited by:

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    5. Diabat, Ali & Bianchessi, Nicola & Archetti, Claudia, 2024. "On the zero-inventory-ordering policy in the inventory routing problem," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1024-1038.
    6. Ziye Tang & Yang Jiao & R. Ravi, 2022. "Combinatorial Heuristics for Inventory Routing Problems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 370-384, January.
    7. Jin-Hwa Song & Martin Savelsbergh, 2007. "Performance Measurement for Inventory Routing," Transportation Science, INFORMS, vol. 41(1), pages 44-54, February.
    8. Mabel C. Chou & Hui Liu & Maurice Queyranne & David Simchi-Levi, 2006. "On the Asymptotic Optimality of a Simple On-Line Algorithm for the Stochastic Single-Machine Weighted Completion Time Problem and Its Extensions," Operations Research, INFORMS, vol. 54(3), pages 464-474, June.
    9. Jaeheon Jung & Kamlesh Mathur, 2007. "An Efficient Heuristic Algorithm for a Two-Echelon Joint Inventory and Routing Problem," Transportation Science, INFORMS, vol. 41(1), pages 55-73, February.
    10. Luca Bertazzi & Lap Mui Ann Chan, 2014. "Analysis of the Best Double Frequency Policy in the Single Link Problem with Discrete Shipping Times," Journal of Optimization Theory and Applications, Springer, vol. 163(1), pages 286-309, October.
    11. 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.
    12. 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.
    13. Hui Liu & Maurice Queyranne & David Simchi‐Levi, 2005. "On the asymptotic optimality of algorithms for the flow shop problem with release dates," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(3), pages 232-242, April.
    14. Anton J. Kleywegt & Vijay S. Nori & Martin W. P. Savelsbergh, 2004. "Dynamic Programming Approximations for a Stochastic Inventory Routing Problem," Transportation Science, INFORMS, vol. 38(1), pages 42-70, February.
    15. Anton J. Kleywegt & Vijay S. Nori & Martin W. P. Savelsbergh, 2002. "The Stochastic Inventory Routing Problem with Direct Deliveries," Transportation Science, INFORMS, vol. 36(1), pages 94-118, February.
    16. J. G. Dai & Gideon Weiss, 2002. "A Fluid Heuristic for Minimizing Makespan in Job Shops," Operations Research, INFORMS, vol. 50(4), pages 692-707, August.
    17. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2012. "Robust Inventory Routing Under Demand Uncertainty," Transportation Science, INFORMS, vol. 46(3), pages 327-340, August.
    18. Zhi-Long Chen & Nicholas G. Hall, 2007. "Supply Chain Scheduling: Conflict and Cooperation in Assembly Systems," Operations Research, INFORMS, vol. 55(6), pages 1072-1089, December.
    19. Philip Kaminsky & David Simchi-Levi, 2001. "The Asymptotic Optimality of the SPT Rule for the Flow Shop Mean Completion Time Problem," Operations Research, INFORMS, vol. 49(2), pages 293-304, April.
    20. Oğuz Solyalı & Haldun Süral, 2011. "A Branch-and-Cut Algorithm Using a Strong Formulation and an A Priori Tour-Based Heuristic for an Inventory-Routing Problem," Transportation Science, INFORMS, vol. 45(3), pages 335-345, August.
    21. Ali Ekici & Okan Örsan Özener & Gültekin Kuyzu, 2015. "Cyclic Delivery Schedules for an Inventory Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 817-829, November.
    22. Miguel Ángel Marfurt Alarcón & Lehilton Lelis Chaves Pedrosa & Fábio Luiz Usberti, 2025. "Fast constructive heuristics for the uncapacitated inventory routing problem," Journal of Heuristics, Springer, vol. 31(2), pages 1-31, June.
    23. Kaminsky, Philip & Kaya, Onur, 2008. "Inventory positioning, scheduling and lead-time quotation in supply chains," International Journal of Production Economics, Elsevier, vol. 114(1), pages 276-293, July.
    24. Sonntag, Danja R. & Schrotenboer, Albert H. & Kiesmüller, Gudrun P., 2023. "Stochastic inventory routing with time-based shipment consolidation," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1186-1201.

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