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Planning capacity and safety stocks in a production-distribution system with multiple products

Foad Ghadimi (UGent) and Tarik Aouam (UGent)
Author
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Abstract
This work jointly optimizes capacity planning and safety stock placement in a production-distribution system under the guaranteed service approach. The network under consideration consists of a manufacturer, a warehouse and a retailer in tandem. The integrated problem sets the capacity of workcenters at the manufacturer and safety stocks at the warehouse and retailer, while taking into account the link between capacity, production cycle times and safety stocks. The relationship between lead times and optimal safety stock placement is characterized in a single workcenter, and efficient solution procedures are developed. These procedures are used in a Lagrangian relaxation algorithm to solve the integrated problem when the manufacturer has multiple workcenters. A simulation framework is presented for setting capacity and safety stocks in the production-distribution system. This framework is used to evaluate the quality of the solutions and the accuracy of the model. A simulation study is conducted to compare the solutions of the proposed integrated approach with two existing approaches for determining capacity and service times and to illustrate the effect of various parameters on the solutions and performance measures of the integrated approach. Computational experiments show that the Lagrangian relaxation algorithm is able to find optimal or near-optimal solutions in reasonable CPU times and outperforms a commercial solver in terms of average optimality gap and run time.
Keywords
Supply chain management, capacity planning, Lagrangian relaxation, safety stocks, guaranteed service approach

Citation

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Chicago
Ghadimi, Foad, and Tarik Aouam. 2019. “Planning Capacity and Safety Stocks in a Production-distribution System with Multiple Products.” In 30th European Conference on Operational Research (EURO2019) : Meeting Abstracts.
APA
Ghadimi, F., & Aouam, T. (2019). Planning capacity and safety stocks in a production-distribution system with multiple products. 30th European Conference on Operational Research (EURO2019) : meeting abstracts. Presented at the 30th European Conference on Operational Research (EURO2019).
Vancouver
1.
Ghadimi F, Aouam T. Planning capacity and safety stocks in a production-distribution system with multiple products. 30th European Conference on Operational Research (EURO2019) : meeting abstracts. 2019.
MLA
Ghadimi, Foad, and Tarik Aouam. “Planning Capacity and Safety Stocks in a Production-distribution System with Multiple Products.” 30th European Conference on Operational Research (EURO2019) : Meeting Abstracts. 2019. Print.
@inproceedings{8622050,
  abstract     = {This work jointly optimizes capacity planning and safety stock placement in a production-distribution system under the guaranteed service approach. The network under consideration consists of a manufacturer, a warehouse and a retailer in tandem. The integrated problem sets the capacity of workcenters at the manufacturer and safety stocks at the warehouse and retailer, while taking into account the link between capacity, production cycle times and safety stocks. The relationship between lead times and optimal safety stock placement is characterized in a single workcenter, and efficient solution procedures are developed. These procedures are used in a Lagrangian relaxation algorithm to solve the integrated problem when the manufacturer has multiple workcenters. A simulation framework is presented for setting capacity and safety stocks in the production-distribution system. This framework is used to evaluate the quality of the solutions and the accuracy of the model. A simulation study is conducted to compare the solutions of the proposed integrated approach with two existing approaches for determining capacity and service times and to illustrate the effect of various parameters on the solutions and performance measures of the integrated approach. Computational experiments show that the Lagrangian relaxation algorithm is able to find optimal or near-optimal solutions in reasonable CPU times and outperforms a commercial solver in terms of average optimality gap and run time.},
  author       = {Ghadimi, Foad and Aouam, Tarik},
  booktitle    = {30th European Conference on Operational Research (EURO2019) : meeting abstracts},
  keywords     = {Supply chain management,capacity planning,Lagrangian relaxation,safety stocks,guaranteed service approach},
  language     = {eng},
  location     = {Dublin},
  title        = {Planning capacity and safety stocks in a production-distribution system with multiple products},
  year         = {2019},
}