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Exact and heuristic methods for a class of selective newsvendor problems with normally distributed demands

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  • Strinka, Zohar M.A.
  • Romeijn, H. Edwin
  • Wu, Jingchen

Abstract

In this paper we study a class of selective newsvendor problems, where a decision maker has a set of raw materials each of which can be customized shortly before satisfying demand. The goal is then to select which subset of customizations maximizes expected profit. We show that certain multi-period and multi-product selective newsvendor problems fall within our problem class. Under the assumption that the demands are independent and normally, but not necessarily identically, distributed we show that some problem instances from our class can be solved efficiently using an attractive sorting property that was also established in the literature for some related problems. For our general model we use the KKT conditions to develop an exact algorithm that is efficient in the number of raw materials. In addition, we develop a class of heuristic algorithms. In a numerical study, we compare the performance of the algorithms, and the heuristics are shown to have excellent performance and running times as compared to available commercial solvers.

Suggested Citation

  • Strinka, Zohar M.A. & Romeijn, H. Edwin & Wu, Jingchen, 2013. "Exact and heuristic methods for a class of selective newsvendor problems with normally distributed demands," Omega, Elsevier, vol. 41(2), pages 250-258.
    • Handle: RePEc:eee:jomega:v:41:y:2013:i:2:p:250-258
    DOI: 10.1016/j.omega.2012.05.004
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    References listed on IDEAS

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    Cited by:

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    3. Mohammad A.M. Abdel-Aal & Mujahid N. Syed & Shokri Z. Selim, 2017. "Multi-product selective newsvendor problem with service level constraints and market selection flexibility," International Journal of Production Research, Taylor & Francis Journals, vol. 55(1), pages 96-117, January.
    4. Merzifonluoglu, Yasemin, 2017. "Integrated demand and procurement portfolio management with spot market volatility and option contracts," European Journal of Operational Research, Elsevier, vol. 258(1), pages 181-192.

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