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Economic Production Lot Sizing Model With Stochastic Demand

Author

Listed:
  • SHINE-DER LEE

    (Department of Industrial and Information Management, National Cheng Kung University, 1 University Road, Tainan, Taiwan, R.O.C)

  • SHU-CHUAN LAN

    (Department of Industrial and Information Management, National Cheng Kung University, 1 University Road, Tainan, Taiwan, R.O.C)

  • CHIN-MING YANG

    (Department of Industrial and Information Management, National Cheng Kung University, 1 University Road, Tainan, Taiwan, R.O.C)

Abstract

We consider the extended economic production quantity (EPQ) problem when demand follows a Poisson process in a production system. A fixed lot sizing policy is implemented to minimize fluctuation of workload, and to smooth production planning and inventory control. The considered costs include setup cost, inventory carrying cost, and shortage cost when demand cannot be satisfied from stock. The main contributions of this paper are two folds. We develop and analyze the extended EPQ model. Under some mild conditions, the expected cost per unit time can be shown to be convex. Via computational experiments, we demonstrate that, in comparison with classical EPQ model, the average reduction of expected cost is significant when demand is random and the proposed model is used to determine lot sizing policy. Our computational tests have also illustrated the impact of various parameters on the expected cost model and the lot sizing policy.

Suggested Citation

  • Shine-Der Lee & Shu-Chuan Lan & Chin-Ming Yang, 2014. "Economic Production Lot Sizing Model With Stochastic Demand," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 31(03), pages 1-23.
    • Handle: RePEc:wsi:apjorx:v:31:y:2014:i:03:n:s0217595914500158
    DOI: 10.1142/S0217595914500158
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    Cited by:

    1. Udayan Chanda & Alok Kumar, 2019. "Optimization of EOQ Model for New Products Under Multi-Stage Adoption Process," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 1-25, April.

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