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Selection, acquisition, and allocation of manufacturing technology in a multi-period environment

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  • Ahmed, Shabbir
  • Sahinidis, Nikolaos V.

Abstract

This paper addresses a multi-period investment problem for selection, acquisition, and allocation of alternative technology choices to meet the demand of a number of product families over a long-range planning horizon. The problem captures the essential features of many existing models for analyzing long-term trade-offs between dedicated and flexible technologies in the chemical, manufacturing, telecommunications, and service industries. We show that the general problem is -hard and present a solution strategy based upon perturbing the linear programming (LP) relaxation solution of a multi-period mixed-integer linear programming formulation for the problem. The key feature of the proposed strategy is a temporal capacity shifting heuristic, whereby capacity expansions are shifted to earlier time periods from amongst those periods chosen for capacity expansion by the LP relaxation solution. With mild assumptions on the problem parameters, we carry a probabilistic analysis which proves that the proposed solution approach is asymptotically optimal almost surely. Our analysis provides a sound theoretical basis for incorporating capacity shifting in existing LP relaxation-based heuristics for long-term technology planning problems in a variety of industries.

Suggested Citation

  • Ahmed, Shabbir & Sahinidis, Nikolaos V., 2008. "Selection, acquisition, and allocation of manufacturing technology in a multi-period environment," European Journal of Operational Research, Elsevier, vol. 189(3), pages 807-821, September.
    • Handle: RePEc:eee:ejores:v:189:y:2008:i:3:p:807-821
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    Cited by:

    1. Weckenborg, Christian & Schumacher, Patrick & Thies, Christian & Spengler, Thomas S., 2024. "Flexibility in manufacturing system design: A review of recent approaches from Operations Research," European Journal of Operational Research, Elsevier, vol. 315(2), pages 413-441.
    2. Mojtaba Farrokh & Ehsan Ahmadi & Minghe Sun, 2023. "A robust stochastic possibilistic programming model for dynamic supply chain network design with pricing and technology selection decisions," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1082-1120, September.
    3. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    4. Jakubovskis, Aldis, 2017. "Strategic facility location, capacity acquisition, and technology choice decisions under demand uncertainty: Robust vs. non-robust optimization approaches," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1095-1104.

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