Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/188466 
Year of Publication: 
2011
Citation: 
[Journal:] Journal of Industrial Engineering and Management (JIEM) [ISSN:] 2013-0953 [Volume:] 4 [Issue:] 3 [Publisher:] OmniaScience [Place:] Barcelona [Year:] 2011 [Pages:] 504-522
Publisher: 
OmniaScience, Barcelona
Abstract: 
Purpose: This paper is concerned with a reverse logistic system where returns are stochastically dependents on sales. The aim of the paper is to assess the influence on optimal production capacities when is assumed that returns are stochastically independent of sales. Design/methodology/approach: This paper presents a model of the system. An approximated model where is assumed that returns are stochastically independent of sales, is formulated to obtain the optimal capacities. The optimal costs of the original and the approximated models are compared in order to assess the influence of the assumption made on returns. Findings: The assumption that returns are stochastically independent of sales is significant in few cases. Research limitations/implications: The impact of the assumption on returns is assessed indirectly, by comparing the optimal costs of both models: the original and approximated. Practical implications: The problem of calculating the optimal capacities in the original model is hard to solve, however in the approximated model the problem is tractable. When the impact of the assumption that returns are stochastically independent of sales is not significant, the approximated model can be used to calculate the optimal capacities of the original model. Originality/value: Prior to this paper, few papers have addressed with the problem of calculating the optimal capacities of reverse logistics systems. The models found in these papers assumed that returns are stochastically independent of sales.
Subjects: 
reverse logistics
remanufacturing
stochastic demand
optimal cost
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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