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An integrated single-item lot-sizing problem in a two-stage industrial symbiosis supply chain with stochastic demands

Cheshmeh Chamani (UGent) , El-Houssaine Aghezzaf (UGent) , Abdelhakim Khatab, Birger Raa (UGent) , Yogang Singh (UGent) and Johannes Cottyn (UGent)
(2021) Advances in production management systems, artificial intelligence for sustainable and resilient production systems, IFIP WG 5.7 International Conference, APMS 2021, proceedings, part II. In IFIP Advances in Information and Communication Technology 631. p.683-693
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Abstract
We consider a two-stage supply chain in which two production plants are collaborating in an industrial symbiosis to satisfy their respective stochastic demands. We formulate the production planning problems of these two plants as an integrated capacitated lot-sizing problem, in which the second production plant uses as an alternative raw material a by-product obtained as a residue from the production of the first plant. The goal is to minimize the overall total cost in the supply chain, including production and inventory of the final product and by-product transfer costs, while meeting the stochastic demands. First, a natural formulation of the problem is proposed, and is solved using the Sample Average Approximation (SAA) method. The analysis of the gaps exhibits however quite large optimality gaps. To improve these optimality gaps, a plant location like reformulation for this integrated lot-sizing problem is developed. The analysis has been carried out again to evaluate both formulations’ performances in terms of the optimality gaps and computational times, both when items demands follow Gamma and Normal distributions. The analysis indicates that despite having a computational time of on average 1.7 times higher than the main formulation, the plant location reformulation provides better optimality gaps on average 22% improved and better ranges for upper and lower bounds under stochastic demands.
Keywords
Lot-sizing, By-product, Industrial symbiosis, Sample average approximation

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MLA
Chamani, Cheshmeh, et al. “An Integrated Single-Item Lot-Sizing Problem in a Two-Stage Industrial Symbiosis Supply Chain with Stochastic Demands.” Advances in Production Management Systems, Artificial Intelligence for Sustainable and Resilient Production Systems, IFIP WG 5.7 International Conference, APMS 2021, Proceedings, Part II, edited by Alexandre Dolgui et al., vol. 631, Springer, 2021, pp. 683–93, doi:10.1007/978-3-030-85902-2_73.
APA
Chamani, C., Aghezzaf, E.-H., Khatab, A., Raa, B., Singh, Y., & Cottyn, J. (2021). An integrated single-item lot-sizing problem in a two-stage industrial symbiosis supply chain with stochastic demands. In A. Dolgui, A. Bernard, D. Lemoine, G. von Cieminski, & D. Romero (Eds.), Advances in production management systems, artificial intelligence for sustainable and resilient production systems, IFIP WG 5.7 International Conference, APMS 2021, proceedings, part II (Vol. 631, pp. 683–693). https://doi.org/10.1007/978-3-030-85902-2_73
Chicago author-date
Chamani, Cheshmeh, El-Houssaine Aghezzaf, Abdelhakim Khatab, Birger Raa, Yogang Singh, and Johannes Cottyn. 2021. “An Integrated Single-Item Lot-Sizing Problem in a Two-Stage Industrial Symbiosis Supply Chain with Stochastic Demands.” In Advances in Production Management Systems, Artificial Intelligence for Sustainable and Resilient Production Systems, IFIP WG 5.7 International Conference, APMS 2021, Proceedings, Part II, edited by Alexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, and David Romero, 631:683–93. Springer. https://doi.org/10.1007/978-3-030-85902-2_73.
Chicago author-date (all authors)
Chamani, Cheshmeh, El-Houssaine Aghezzaf, Abdelhakim Khatab, Birger Raa, Yogang Singh, and Johannes Cottyn. 2021. “An Integrated Single-Item Lot-Sizing Problem in a Two-Stage Industrial Symbiosis Supply Chain with Stochastic Demands.” In Advances in Production Management Systems, Artificial Intelligence for Sustainable and Resilient Production Systems, IFIP WG 5.7 International Conference, APMS 2021, Proceedings, Part II, ed by. Alexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, and David Romero, 631:683–693. Springer. doi:10.1007/978-3-030-85902-2_73.
Vancouver
1.
Chamani C, Aghezzaf E-H, Khatab A, Raa B, Singh Y, Cottyn J. An integrated single-item lot-sizing problem in a two-stage industrial symbiosis supply chain with stochastic demands. In: Dolgui A, Bernard A, Lemoine D, von Cieminski G, Romero D, editors. Advances in production management systems, artificial intelligence for sustainable and resilient production systems, IFIP WG 57 International Conference, APMS 2021, proceedings, part II. Springer; 2021. p. 683–93.
IEEE
[1]
C. Chamani, E.-H. Aghezzaf, A. Khatab, B. Raa, Y. Singh, and J. Cottyn, “An integrated single-item lot-sizing problem in a two-stage industrial symbiosis supply chain with stochastic demands,” in Advances in production management systems, artificial intelligence for sustainable and resilient production systems, IFIP WG 5.7 International Conference, APMS 2021, proceedings, part II, Nantes, FRANCE, 2021, vol. 631, pp. 683–693.
@inproceedings{8733149,
  abstract     = {{We consider a two-stage supply chain in which two production plants are collaborating in an industrial symbiosis to satisfy their respective stochastic demands. We formulate the production planning problems of these two plants as an integrated capacitated lot-sizing problem, in which the second production plant uses as an alternative raw material a by-product obtained as a residue from the production of the first plant. The goal is to minimize the overall total cost in the supply chain, including production and inventory of the final product and by-product transfer costs, while meeting the stochastic demands. First, a natural formulation of the problem is proposed, and is solved using the Sample Average Approximation (SAA) method. The analysis of the gaps exhibits however quite large optimality gaps. To improve these optimality gaps, a plant location like reformulation for this integrated lot-sizing problem is developed. The analysis has been carried out again to evaluate both formulations’ performances in terms of the optimality gaps and computational times, both when items demands follow Gamma and Normal distributions. The analysis indicates that despite having a computational time of on average 1.7 times higher than the main formulation, the plant location reformulation provides better optimality gaps on average 22% improved and better ranges for upper and lower bounds under stochastic demands.}},
  author       = {{Chamani, Cheshmeh and Aghezzaf, El-Houssaine and Khatab, Abdelhakim and Raa, Birger and Singh, Yogang and Cottyn, Johannes}},
  booktitle    = {{Advances in production management systems, artificial intelligence for sustainable and resilient production systems, IFIP WG 5.7 International Conference, APMS 2021, proceedings, part II}},
  editor       = {{Dolgui, Alexandre and Bernard, Alain and Lemoine, David and von Cieminski, Gregor and Romero, David}},
  isbn         = {{9783030859015}},
  issn         = {{1868-4238}},
  keywords     = {{Lot-sizing,By-product,Industrial symbiosis,Sample average approximation}},
  language     = {{eng}},
  location     = {{Nantes, FRANCE}},
  pages        = {{683--693}},
  publisher    = {{Springer}},
  title        = {{An integrated single-item lot-sizing problem in a two-stage industrial symbiosis supply chain with stochastic demands}},
  url          = {{http://doi.org/10.1007/978-3-030-85902-2_73}},
  volume       = {{631}},
  year         = {{2021}},
}
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