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The integrated stochastic lot-sizing and job-shop scheduling problem in closed-loop supply chains

Author

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  • Milad Mohammadi

Abstract

This research develops a mathematical model for the integrated lot-sizing and job-shop scheduling problem in which supplier selection and purchase lot-sizing are incorporated into the production lot-sizing problem. A Chance Constrained Programming (CCP) approach is applied to formulate them in a General Lot-sizing and Scheduling Problem (GLSP) model. Some numerical experiments are performed to evaluate the efficiency of the model’s results. The computational analysis indicates that when the production and purchase lot-sizing decisions are taken simultaneously, combined cost of production and purchase (and thus the total cost) is lower than when these decisions are made hierarchically. The average cost of the integrated model is 4.03% less than the non-integrated model. This improvement is mostly made in the purchase lot-sizing cost because through applying the integrated model, the company can recognize the best time of procuring materials from the best suppliers and use their discount schemes.

Suggested Citation

  • Milad Mohammadi, 2025. "The integrated stochastic lot-sizing and job-shop scheduling problem in closed-loop supply chains," Journal of Management Analytics, Taylor & Francis Journals, vol. 12(4), pages 882-905, October.
    • Handle: RePEc:taf:tjmaxx:v:12:y:2025:i:4:p:882-905
    DOI: 10.1080/23270012.2025.2472371
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