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Flow Shop Scheduling with Resource Flexibility

Author

Listed:
  • Richard L. Daniels

    (Georgia Institute of Technology, Atlanta, Georgia)

  • Joseph B. Mazzola

    (Duke University, Durham, North Carolina)

Abstract

This paper explores the improvements in manufacturing efficiency that can be achieved by broadening the scope of production scheduling to include both the sequencing of work and the coordination of the resource inputs required to perform work. Recognizing that some resources are inherently flexible and thus can be reassigned dynamically to processing centers as needed, and that job processing times are often a function of the amount of resource dedicated to specific operations, we formulate the flexible-resource scheduling problem with the objective of simultaneously determining the permutation job sequence, resource allocation policy, and operation start times that optimize system performance. Focusing on flexible-resource scheduling in flow shop production systems, we discuss problem complexity, identify properties of and establish lower bounds for optimal schedules, develop optimal and heuristic solution approaches, and report the results of extensive computational experimentation designed to explore the operational benefits of resource flexibility. The computational results demonstrate that the performance improvements associated with flexible-resource scheduling are substantial, and suggest that the heuristic provides an effective means for solving larger problems.

Suggested Citation

  • Richard L. Daniels & Joseph B. Mazzola, 1994. "Flow Shop Scheduling with Resource Flexibility," Operations Research, INFORMS, vol. 42(3), pages 504-522, June.
  • Handle: RePEc:inm:oropre:v:42:y:1994:i:3:p:504-522
    DOI: 10.1287/opre.42.3.504
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    Citations

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    Cited by:

    1. Dayal Madhukar & Verma, Sanjay, 2015. "Multi-processor Exact Procedures for Regular Measures of the Multi-mode RCPSP," IIMA Working Papers WP2015-03-25, Indian Institute of Management Ahmedabad, Research and Publication Department.
    2. Akhil Kumar & J. Leon Zhao, 1999. "Dynamic Routing and Operational Controls in Workflow Management Systems," Management Science, INFORMS, vol. 45(2), pages 253-272, February.
    3. Figielska, Ewa, 2014. "A heuristic for scheduling in a two-stage hybrid flowshop with renewable resources shared among the stages," European Journal of Operational Research, Elsevier, vol. 236(2), pages 433-444.
    4. Huq, Faizul & Cutright, Kenneth & Martin, Clarence, 2004. "Employee scheduling and makespan minimization in a flow shop with multi-processor work stations: a case study," Omega, Elsevier, vol. 32(2), pages 121-129, April.
    5. Richard L. Daniels & Joseph B. Mazzola & Dailun Shi, 2004. "Flow Shop Scheduling with Partial Resource Flexibility," Management Science, INFORMS, vol. 50(5), pages 658-669, May.
    6. Olivier Guyon & Pierre Lemaire & Éric Pinson & David Rivreau, 2014. "Solving an integrated job-shop problem with human resource constraints," Annals of Operations Research, Springer, vol. 213(1), pages 147-171, February.
    7. Miloš Milenković & Susana Val & Nebojša Bojović, 2023. "Simultaneous lot sizing and scheduling in the animal feed premix industry," Operational Research, Springer, vol. 23(2), pages 1-40, June.
    8. Gultekin, Hakan, 2012. "Scheduling in flowshops with flexible operations: Throughput optimization and benefits of flexibility," International Journal of Production Economics, Elsevier, vol. 140(2), pages 900-911.

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