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Capacity Acquisition and Disposal with Discrete Facility Sizes

Author

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  • S. Rajagopalan

    (Department of Information and Operations Management, School of Business Administration, University of Southern California, Los Angeles, California 90089)

  • Andreas C. Soteriou

    (Department of Information and Operations Management, School of Business Administration, University of Southern California, Los Angeles, California 90089)

Abstract

We consider some key features of capacity acquisition, disposal, and replacement decisions in this paper that are seldom captured in capacity expansion models in the literature. First, capacity is often purchased in the form of equipment which comes only in a few discrete sizes. Second, some or all of the capacity may be replaced periodically due to the availability of better and cheaper equipment, or due to deterioration and increased operating costs of older equipment. Finally, some capacity may be disposed due to declining demand. We present integer programming formulations that model all of these aspects. We identify special structures in these formulations that are then exploited to develop efficient procedures for solving the linear relaxation optimally. The solution to the linear relaxation together with a heuristic interchange procedure are used in a branch-and-bound procedure to obtain optimal solutions. Computational results are presented that establish the effectiveness of the procedures in solving realistic problems to optimality.

Suggested Citation

  • S. Rajagopalan & Andreas C. Soteriou, 1994. "Capacity Acquisition and Disposal with Discrete Facility Sizes," Management Science, INFORMS, vol. 40(7), pages 903-917, July.
    • Handle: RePEc:inm:ormnsc:v:40:y:1994:i:7:p:903-917
    DOI: 10.1287/mnsc.40.7.903
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    Citations

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    Cited by:

    1. Bricha, Naji & Nourelfath, Mustapha, 2014. "Extra-capacity versus protection for supply networks under attack," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 185-196.
    2. Giovanni Pantuso & Kjetil Fagerholt & Stein W. Wallace, 2016. "Uncertainty in Fleet Renewal: A Case from Maritime Transportation," Transportation Science, INFORMS, vol. 50(2), pages 390-407, May.
    3. Martínez-Costa, Carme & Mas-Machuca, Marta & Benedito, Ernest & Corominas, Albert, 2014. "A review of mathematical programming models for strategic capacity planning in manufacturing," International Journal of Production Economics, Elsevier, vol. 153(C), pages 66-85.
    4. Hadjinicola, George C. & Soteriou, Andreas C., 2003. "Reducing the cost of defects in multistage production systems: A budget allocation perspective," European Journal of Operational Research, Elsevier, vol. 145(3), pages 621-634, March.
    5. James Luedtke & George L. Nemhauser, 2009. "Strategic Planning with Start-Time Dependent Variable Costs," Operations Research, INFORMS, vol. 57(5), pages 1250-1261, October.
    6. Lim, Seung-Kil & Kim, Yeong-Dae, 1998. "Capacity planning for phased implementation of flexible manufacturing systems under budget restrictions," European Journal of Operational Research, Elsevier, vol. 104(1), pages 175-186, January.
    7. Mørch, Ove & Fagerholt, Kjetil & Pantuso, Giovanni & Rakke, Jørgen, 2017. "Maximizing the rate of return on the capital employed in shipping capacity renewal," Omega, Elsevier, vol. 67(C), pages 42-53.
    8. Amiri, Ali, 2002. "An integrated approach for planning the adoption of client/server systems," European Journal of Operational Research, Elsevier, vol. 142(3), pages 509-522, November.
    9. Bing Lin & Shaoxiang Chen & Yi Feng & Jianjun Xu, 2018. "The Joint Stock and Capacity Rationings of a Make-To-Stock System with Flexible Demand," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(01), pages 1-27, February.
    10. Joseph, Anito & Gass, Saul I. & Bryson, Noel, 1998. "An objective hyperplane search procedure for solving the general all-integer linear programming (ILP) problem," European Journal of Operational Research, Elsevier, vol. 104(3), pages 601-614, February.
    11. Rajagopalan, S. & Yu, Hung-Liang, 2001. "Capacity planning with congestion effects," European Journal of Operational Research, Elsevier, vol. 134(2), pages 365-377, October.
    12. Manu Goyal & Serguei Netessine, 2011. "Volume Flexibility, Product Flexibility, or Both: The Role of Demand Correlation and Product Substitution," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 180-193, March.
    13. Alexandar Angelus & Evan L. Porteus, 2002. "Simultaneous Capacity and Production Management of Short-Life-Cycle, Produce-to-Stock Goods Under Stochastic Demand," Management Science, INFORMS, vol. 48(3), pages 399-413, March.
    14. Pantuso Giovanni, 2017. "The Football Team Composition Problem: a Stochastic Programming approach," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(3), pages 113-129, September.
    15. Bricha, Naji & Nourelfath, Mustapha, 2015. "Protection of warehouses and plants under capacity constraint," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 93-104.
    16. Poretus, Evan L. & Angelus, Alexander, 2000. "Simultaneous Production and Capacity Management under Stochastic Demand for Perishable Goods," Research Papers 1419r, Stanford University, Graduate School of Business.
    17. Vernon Ning Hsu, 2002. "Dynamic Capacity Expansion Problem with Deferred Expansion and Age-Dependent Shortage Cost," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 44-54, June.
    18. Chand, Suresh & McClurg, Tim & Ward, Jim, 2000. "A model for parallel machine replacement with capacity expansion," European Journal of Operational Research, Elsevier, vol. 121(3), pages 519-531, March.

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