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A multiple-item budget-constraint newsboy problem with a reservation policy


  • Chen, Liang-Hsuan
  • Chen, Ying-Che


In contrast to the classical newsboy-style problem, this paper develops a model for the multiple-item budget-constraint newsboy problem considering a reservation policy to meet marketing needs. A discount rate is provided to those customers who are willing to make a reservation. In addition to the demand from the original customers, extra demand is also included in the model due to the motivation of the discount rate. A solution algorithm, namely the MCR algorithm, is proposed to solve the problem. The proposed algorithm can actually be considered as a generalization of the classical newsboy-style problem. The MCR algorithm not only provides a business unit with the optimal order quantity, but also the discount rate necessary to achieve the maximal total expected profit under a limited budget. From the illustrated example, it is shown that the expected profit from the proposed model is greater than that from the classical model, due to the consideration of reservations, even though the budget constraint is tight. The increase in the expected profit could be treated as an information value from the willingness function. Although the proposed model is developed for multiple-item problems, it also can be applied to single-item ones. From the sensitivity analysis, the application of the single-item problem to the proposed model can still obtain greater expected profit than the classical model under different budgetary levels.

Suggested Citation

  • Chen, Liang-Hsuan & Chen, Ying-Che, 2010. "A multiple-item budget-constraint newsboy problem with a reservation policy," Omega, Elsevier, vol. 38(6), pages 431-439, December.
  • Handle: RePEc:eee:jomega:v:38:y:2010:i:6:p:431-439

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    References listed on IDEAS

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    Cited by:

    1. Khanra, Avijit & Soman, Chetan, 2013. "Sensitivity Analysis of the Newsboy Model," IIMA Working Papers WP2013-09-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    2. Roy, Arpita & Sana, Shib Sankar & Chaudhuri, Kripasindhu, 2012. "Optimal replenishment order for uncertain demand in three layer supply chain," Economic Modelling, Elsevier, vol. 29(6), pages 2274-2282.
    3. Zhang, Bin, 2012. "Multi-tier binary solution method for multi-product newsvendor problem with multiple constraints," European Journal of Operational Research, Elsevier, vol. 218(2), pages 426-434.
    4. Serel, Do─čan A., 2012. "Multi-item quick response system with budget constraint," International Journal of Production Economics, Elsevier, vol. 137(2), pages 235-249.
    5. Khanra, Avijit & Soman, Chetan & Bandyopadhyay, Tathagata, 2014. "Sensitivity analysis of the newsvendor model," European Journal of Operational Research, Elsevier, vol. 239(2), pages 403-412.
    6. repec:kap:netspa:v:17:y:2017:i:2:d:10.1007_s11067-016-9333-y is not listed on IDEAS
    7. Qiang, Qiang & Ke, Ke & Anderson, Trisha & Dong, June, 2013. "The closed-loop supply chain network with competition, distribution channel investment, and uncertainties," Omega, Elsevier, vol. 41(2), pages 186-194.
    8. Halkos, George & Kevork, Ilias, 2012. "Validity and precision of estimates in the classical newsvendor model with exponential and rayleigh demand," MPRA Paper 36460, University Library of Munich, Germany.
    9. Halkos, George & Kevork, Ilias, 2012. "Evaluating alternative estimators for optimal order quantities in the newsvendor model with skewed demand," MPRA Paper 36205, University Library of Munich, Germany.
    10. Tang, Dong, 2011. "Managing finished-goods inventory under capacitated delayed differentiation," Omega, Elsevier, vol. 39(5), pages 481-492, October.
    11. Banerjee, Pradeep K. & Turner, T. Rolf, 2012. "A flexible model for the pricing of perishable assets," Omega, Elsevier, vol. 40(5), pages 533-540.
    12. Huang, Di & Zhou, Hong & Zhao, Qiu-Hong, 2011. "A competitive multiple-product newsboy problem with partial product substitution," Omega, Elsevier, vol. 39(3), pages 302-312, June.


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