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A multi-period ordering and clearance pricing model considering the competition between new and out-of-season products

Author

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  • Xiang Li

    (Nankai University)

  • Guohua Sun

    (Shandong University of Finance and Economics)

  • Yongjian Li

    (Nankai University)

Abstract

The joint management of pricing and inventory for perishable products has become an important problem for retailers. This paper investigates a multi-period ordering and clearance pricing model under consideration of the competition between new and out-of-season products. In each period, the ordering quantity of the new product and the clearance price of the out-of-season product are determined as decision variables before the demand is realized, and the unsold new product becomes the out-of-season one of the next period. We establish a finite-horizon Markov decision process model to formulate this problem and analyze its properties. A traditional dynamic program (DP) approach with two-dimensional search is provided. In addition, a myopic policy is derived in which only the profit of the current period is considered. Finally, we apply genetic algorithm (GA) to this problem and design a GA-based heuristic approach, showing by comparison among different algorithms that the GA-based heuristic approach is more performance sound than the myopic policy and much less time consuming than the DP approach.

Suggested Citation

  • Xiang Li & Guohua Sun & Yongjian Li, 2016. "A multi-period ordering and clearance pricing model considering the competition between new and out-of-season products," Annals of Operations Research, Springer, vol. 242(2), pages 207-221, July.
    • Handle: RePEc:spr:annopr:v:242:y:2016:i:2:d:10.1007_s10479-013-1498-x
    DOI: 10.1007/s10479-013-1498-x
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    Cited by:

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    2. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    3. Liu, Jiaguo & Zhao, Huida & Li, Jian & Yue, Xiaohang, 2021. "Operational strategy of customized bus considering customers’ variety seeking behavior and service level," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Kannan Govindan, 2016. "Evolutionary algorithms for supply chain management," Annals of Operations Research, Springer, vol. 242(2), pages 195-206, July.
    5. Zhou, Shenghan & Zhou, Yuliang & Zuo, Xiaorong & Xiao, Yiyong & Cheng, Yang, 2018. "Modeling and solving the constrained multi-items lot-sizing problem with time-varying setup cost," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 202-207.

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