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Optimal Replenishment Policy for Deteriorating Products in a Newsboy Problem with Multiple Just-in-Time Deliveries

Author

Listed:
  • Abu Hashan Md Mashud

    (Department of Mathematics, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh)

  • Hui-Ming Wee

    (Department of Industrial and Systems Engineering, Chung Yuan Christian University, Chungli 32023, Taiwan)

  • Chiao-Ven Huang

    (Department of Industrial and Systems Engineering, Chung Yuan Christian University, Chungli 32023, Taiwan)

  • Jei-Zheng Wu

    (Department of Business Administration, Soochow University, 56 Section 1, Kuei-yang Street, Taipei 10048, Taiwan
    If you are interested or have any doubt of this article, please contact Jei-Zheng Wu ( jzwu@scu.edu.tw ) first.)

Abstract

Product deterioration is a common phenomenon and is overlooked in most contemporary research on the newsboy problem. In this study, we have considered product deterioration in a production–inventory newsboy model based on multiple just-in-time (JIT) deliveries. This model is solved by a classical optimization technique for the manufacturer production size, wholesale price, replenishment plan, and retailer order policy using a distribution-free approach. Moreover, in order to improve business and entice more customers, a return policy and a post-sale warranty policy is adopted in the model. Theoretical development and numerical examples are provided to demonstrate the validity of this approach.

Suggested Citation

  • Abu Hashan Md Mashud & Hui-Ming Wee & Chiao-Ven Huang & Jei-Zheng Wu, 2020. "Optimal Replenishment Policy for Deteriorating Products in a Newsboy Problem with Multiple Just-in-Time Deliveries," Mathematics, MDPI, vol. 8(11), pages 1-18, November.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:11:p:1981-:d:441096
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    References listed on IDEAS

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    Cited by:

    1. Rung-Hung Su & Dong-Yuh Yang & He-Jhen Lin & Yu-Cheng Yang, 2023. "Estimating conservative profitability of a newsboy-type product with exponentially distributed demand based on multiple samples," Annals of Operations Research, Springer, vol. 322(2), pages 967-989, March.

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