Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/195612 
Year of Publication: 
2018
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 14 [Issue:] 2 [Publisher:] Springer [Place:] Heidelberg [Year:] 2018 [Pages:] 367-382
Publisher: 
Springer, Heidelberg
Abstract: 
Decentralized supply chain management is found to be significantly relevant in today's competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem's convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy approach and chance constraint approach. Ultimately, a numerical example is constructed and worked through to demonstrate applicability of the optimization model. A sensitivity analysis is also made.
Subjects: 
Decentralized supply chain
Production-distribution planning problem
Bi-level approach
Network design
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size
943.55 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.