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Scheduling Parallel Manufacturing Cells with Resource Flexibility

Author

Listed:
  • Richard L. Daniels

    (School of Management, Georgia Institute of Technology, Atlanta, Georgia 30332-0520)

  • Barbara J. Hoopes

    (Pamplin College of Business, Virginia Polytechnic Institute and State University, Falls Church, Virginia 22042)

  • Joseph B. Mazzola

    (Fuqua School of Business, Duke University, Durham, North Carolina 27706)

Abstract

This paper investigates the improvements in manufacturing performance that can be realized by broadening the scope of the production scheduling function to include both job sequencing and processing-time control through the deployment of a flexible resource. We consider an environment in which a set of jobs must be scheduled over a set of parallel manufacturing cells, each consisting of a single machine, where the processing time of each job depends on the amount of resource allocated to the associated cell. Two versions of the problem are introduced: a static problem in which a single resource-allocation decision is made and maintained throughout the production horizon, and a dynamic problem in which resource can be reassigned among the production cells as local bottlenecks shift. We provide mathematical formulations for each version of the problem, establish problem complexity, identify important characteristics of optimal solutions, develop optimal and heuristic solution approaches, and report the results of a set of computational experiments. The computational results demonstrate that substantial improvements in operational performance can be achieved through effective utilization of resource flexibility.

Suggested Citation

  • Richard L. Daniels & Barbara J. Hoopes & Joseph B. Mazzola, 1996. "Scheduling Parallel Manufacturing Cells with Resource Flexibility," Management Science, INFORMS, vol. 42(9), pages 1260-1276, September.
    • Handle: RePEc:inm:ormnsc:v:42:y:1996:i:9:p:1260-1276
    DOI: 10.1287/mnsc.42.9.1260
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    Citations

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    Cited by:

    1. Norelhouda Sekkal & Fayçal Belkaid, 2020. "A multi-objective simulated annealing to solve an identical parallel machine scheduling problem with deterioration effect and resources consumption constraints," Journal of Combinatorial Optimization, Springer, vol. 40(3), pages 660-696, October.
    2. Geurtsen, M. & Didden, Jeroen B.H.C. & Adan, J. & Atan, Z. & Adan, I., 2023. "Production, maintenance and resource scheduling: A review," European Journal of Operational Research, Elsevier, vol. 305(2), pages 501-529.
    3. Albino, Vito & Claudio Garavelli, A., 1999. "Limited flexibility in cellular manufacturing systems: A simulation study," International Journal of Production Economics, Elsevier, vol. 60(1), pages 447-455, April.
    4. Su, Ling-Huey & Lien, Chun-Yuan, 2009. "Scheduling parallel machines with resource-dependent processing times," International Journal of Production Economics, Elsevier, vol. 117(2), pages 256-266, February.
    5. Norelhouda Sekkal & Fayçal Belkaid, 0. "A multi-objective simulated annealing to solve an identical parallel machine scheduling problem with deterioration effect and resources consumption constraints," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-37.
    6. Puay Khoon Toh & Gautam Ahuja, 2022. "Integration and appropriability: A study of process and product components within a firm's innovation portfolio," Strategic Management Journal, Wiley Blackwell, vol. 43(6), pages 1075-1109, June.
    7. Edis, Emrah B. & Oguz, Ceyda & Ozkarahan, Irem, 2013. "Parallel machine scheduling with additional resources: Notation, classification, models and solution methods," European Journal of Operational Research, Elsevier, vol. 230(3), pages 449-463.
    8. Ruiz-Torres, Alex J. & Lopez, Francisco J. & Ho, Johnny C., 2007. "Scheduling uniform parallel machines subject to a secondary resource to minimize the number of tardy jobs," European Journal of Operational Research, Elsevier, vol. 179(2), pages 302-315, June.
    9. Kayan, Rabia K. & Akturk, M. Selim, 2005. "A new bounding mechanism for the CNC machine scheduling problems with controllable processing times," European Journal of Operational Research, Elsevier, vol. 167(3), pages 624-643, December.
    10. Garavelli, A. Claudio, 2001. "Performance analysis of a batch production system with limited flexibility," International Journal of Production Economics, Elsevier, vol. 69(1), pages 39-48, January.
    11. 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.
    12. Mohamed Amine Abdeljaoued & Nour El Houda Saadani & Zied Bahroun, 2020. "Heuristic and metaheuristic approaches for parallel machine scheduling under resource constraints," Operational Research, Springer, vol. 20(4), pages 2109-2132, December.

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