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A robust optimisation model for production planning and pricing under demand uncertainty

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Listed:
  • Ehsan Ardjmand
  • Gary R. Weckman
  • William A. Young
  • Omid Sanei Bajgiran
  • Bizhan Aminipour

Abstract

The profitability of every manufacturing plant is dependent on its pricing strategy and a production plan to support the customers’ demand. In this paper, a new robust multi-product and multi-period model for planning and pricing is proposed. The demand is considered to be uncertain and price-dependent. Thus, for each price, a range of demands is possible. The unsatisfied demand is considered to be lost and hence, no backlogging is allowed. The objective is to maximise the profit over the planning horizon, which consists of a finite number of periods. To solve the proposed model, a modified unconscious search (US) algorithm is introduced. Several artificial test problems along with a real case implementation of the model in a textile manufacturing plant are used to show the applicability of the model and effectiveness of the US for tackling this problem. The results show that the proposed model can improve the profitability of the plant and the US is able to find high quality solutions in a very short time compared to exact methods.

Suggested Citation

  • Ehsan Ardjmand & Gary R. Weckman & William A. Young & Omid Sanei Bajgiran & Bizhan Aminipour, 2016. "A robust optimisation model for production planning and pricing under demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3885-3905, July.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:13:p:3885-3905
    DOI: 10.1080/00207543.2016.1161251
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    3. Xide Zhu & Peijun Guo, 2020. "Bilevel programming approaches to production planning for multiple products with short life cycles," 4OR, Springer, vol. 18(2), pages 151-175, June.
    4. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2020. "Tactical sales and operations planning: A holistic framework and a literature review of decision-making models," International Journal of Production Economics, Elsevier, vol. 228(C).
    5. Viktoryia Buhayenko & Dick den Hertog, 2017. "Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6801-6823, November.

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