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Optimal design of multi-echelon supply chain networks under normally distributed demand

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  • Konstantinos Petridis

Abstract

This paper addresses the optimal design of a multiproduct, multi-echelon supply network under uncertainty of demand. The network consists of multiproduct production sites, warehouses and distribution centers and decisions about the selection of facilities and their capacity are taken. Furthermore, information about the flows of products transferred and the safety stock at each distribution center is derived. The lead time of an order to a customer is computed, using the probabilities of overstocking and understocking. All these decisions are incorporated into a single period mixed integer non-linear programming problem (MINLP) which minimizes cost. Linearization techniques for selected highly non-linear terms of the models are explored in order to reduce the computational effort for the solution of the model. Finally, a sensitivity analysis is performed by changing product demand parameters and assessing their effect on the supply chain structure. Copyright Springer Science+Business Media New York 2015

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  • Konstantinos Petridis, 2015. "Optimal design of multi-echelon supply chain networks under normally distributed demand," Annals of Operations Research, Springer, vol. 227(1), pages 63-91, April.
    • Handle: RePEc:spr:annopr:v:227:y:2015:i:1:p:63-91:10.1007/s10479-013-1420-6
    DOI: 10.1007/s10479-013-1420-6
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    2. Aaron Guerrero Campanur & Elias Olivares-Benitez & Pablo A. Miranda & Rodolfo Eleazar Perez-Loaiza & Jose Humberto Ablanedo-Rosas, 2018. "Design of a Logistics Nonlinear System for a Complex, Multiechelon, Supply Chain Network with Uncertain Demands," Complexity, Hindawi, vol. 2018, pages 1-16, November.
    3. Barros, Júlio & Cortez, Paulo & Carvalho, M. Sameiro, 2021. "A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process," Operations Research Perspectives, Elsevier, vol. 8(C).
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    5. De, Arijit & Mogale, D.G. & Zhang, Mengdi & Pratap, Saurabh & Kumar, Sri Krishna & Huang, George Q., 2020. "Multi-period multi-echelon inventory transportation problem considering stakeholders behavioural tendencies," International Journal of Production Economics, Elsevier, vol. 225(C).
    6. Yi Liao & Ali Diabat & Chaher Alzaman & Yiqiang Zhang, 2020. "Modeling and heuristics for production time crashing in supply chain network design," Annals of Operations Research, Springer, vol. 288(1), pages 331-361, May.
    7. Alzaman, Chaher & Zhang, Zhi-Hai & Diabat, Ali, 2018. "Supply chain network design with direct and indirect production costs: Hybrid gradient and local search based heuristics," International Journal of Production Economics, Elsevier, vol. 203(C), pages 203-215.
    8. Shuihua Han & Yue Jiang & Ling Zhao & Stephen C. H. Leung & Zongwei Luo, 2020. "Weight reduction technology and supply chain network design under carbon emission restriction," Annals of Operations Research, Springer, vol. 290(1), pages 567-590, July.
    9. Iman Kazemian & Samin Aref, 2016. "Multi-echelon Supply Chain Flexibility Enhancement Through Detecting Bottlenecks," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 17(4), pages 357-372, December.
    10. Konstantinos Petridis & Garyfallos Arabatzis & Angelo Sifaleras, 2020. "Mathematical optimization models for fuelwood production," Annals of Operations Research, Springer, vol. 294(1), pages 59-74, November.
    11. Ardavan Babaei & Majid Khedmati & Mohammad Reza Akbari Jokar, 2023. "A new branch and efficiency algorithm for an optimal design of the supply chain network in view of resilience, inequity and traffic congestion," Annals of Operations Research, Springer, vol. 321(1), pages 49-78, February.
    12. Peyman Taki & Farnaz Barzinpour & Ebrahim Teimoury, 2016. "Risk-pooling strategy, lead time, delivery reliability and inventory control decisions in a stochastic multi-objective supply chain network design," Annals of Operations Research, Springer, vol. 244(2), pages 619-646, September.

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