Campus Units

Industrial and Manufacturing Systems Engineering, Bioeconomy Institute (BEI)

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

3-11-2020

Journal or Book Title

Computers & Industrial Engineering

First Page

106397

Research Focus Area(s)

​Operations Research

DOI

10.1016/j.cie.2020.106397

Abstract

This paper proposes an integrated model for a multi-period reverse logistics (RL) network design problem under return and demand uncertainty. The reverse logistics network is modeled as a two-stage stochastic programming model to make strategic and tactical decisions. The strategic decisions are the first stage decisions in establishing network’s facilities and tactical decisions are the second stage decisions on material flow, inventory, backorder, shortage, and outsourcing. The uncertainties considered in this study are the primary market return and secondary market demand. The model aims to determine optimal numbers of sorting centers and warehouses, optimal lot sizes, and transportation plan that minimize the expected total system cost over the planning horizon. A case study was conducted to validate the proposed model. Numerical results indicate that the stochastic model solution outperforms result of expected value solution.

Comments

This is a manuscript of an article published as Azizi, Vahid, Guiping Hu, and Mahsa Mokari. "A two-stage stochastic programming model for multi-period reverse logistics network design with lot-sizing." Computers & Industrial Engineering (2020): 106397. DOI: 10.1016/j.cie.2020.106397. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier Ltd.

Language

en

File Format

application/pdf

Available for download on Saturday, March 11, 2023

Published Version

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