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Integer programming models for mid-term production planning for high-tech low-volume supply chains

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  • de Kruijff, Joost T.
  • Hurkens, Cor A.J.
  • de Kok, Ton G.

Abstract

This paper studies the mid-term production planning of high-tech low-volume industries. Mid-term production planning (6 to 24 months) allocates the capacity of production resources to different products over time and coordinates the associated inventories and material inputs so that known or predicted demand is met in the best possible manner. High-tech low-volume industries can be characterized by the limited production quantities and the complexity of the supply chain. To model this, we introduce a mixed integer linear programming model that can handle general supply chains and production processes that require multiple resources. Furthermore, it supports semi-flexible capacity constraints and multiple production modes.

Suggested Citation

  • de Kruijff, Joost T. & Hurkens, Cor A.J. & de Kok, Ton G., 2018. "Integer programming models for mid-term production planning for high-tech low-volume supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 984-997.
    • Handle: RePEc:eee:ejores:v:269:y:2018:i:3:p:984-997
    DOI: 10.1016/j.ejor.2018.02.049
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    References listed on IDEAS

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    1. Hubert Missbauer & Reha Uzsoy, 2011. "Optimization Models of Production Planning Problems," International Series in Operations Research & Management Science, in: Karl G. Kempf & Pınar Keskinocak & Reha Uzsoy (ed.), Planning Production and Inventories in the Extended Enterprise, chapter 0, pages 437-507, Springer.
    2. Spitter, J. M. & Hurkens, C. A. J. & de Kok, A. G. & Lenstra, J. K. & Negenman, E. G., 2005. "Linear programming models with planned lead times for supply chain operations planning," European Journal of Operational Research, Elsevier, vol. 163(3), pages 706-720, June.
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    6. Kolisch, Rainer, 2000. "Integration of assembly and fabrication for make-to-order production," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 335, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Rahmaniani, Ragheb & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2017. "The Benders decomposition algorithm: A literature review," European Journal of Operational Research, Elsevier, vol. 259(3), pages 801-817.
    8. Weglarz, Jan & Józefowska, Joanna & Mika, Marek & Waligóra, Grzegorz, 2011. "Project scheduling with finite or infinite number of activity processing modes - A survey," European Journal of Operational Research, Elsevier, vol. 208(3), pages 177-205, February.
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    Cited by:

    1. Bing Feng & Kaiyang Sun & Min Chen & Tao Gao, 2020. "The Impact of Core Technological Capabilities of High-Tech Industry on Sustainable Competitive Advantage," Sustainability, MDPI, vol. 12(7), pages 1-15, April.
    2. Eduardo Gutiérrez González & Olga Vladimirovna Panteleeva, 2020. "A model for planning and optimizing an engineering company production," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 669-699, September.

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