A stochastic optimization model for integrated forward/reverse logistics network design

In this paper, we develop a stochastic programming model for an integrated forward/reverse logistics network design under uncertainty. First, an efficient deterministic mixed integer linear programming model is developed for integrated logistics network design to avoid the sub-optimality caused by t...

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Bibliographic Details
Published in:Journal of manufacturing systems Vol. 28; no. 4; pp. 107 - 114
Main Authors: Pishvaee, Mir Saman, Jolai, Fariborz, Razmi, Jafar
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.12.2009
Elsevier
Subjects:
Applied sciences
Exact sciences and technology
Flows in networks. Combinatorial problems
Logistics
Mathematical programming
Operational research and scientific management
Operational research. Management science
Stochastic model
Script
Probabilistic approach
Data handling
Mixed integer programming
Modeling
Recovery
Linear model
Stochastic programming
Engineering design
Uncertain system
Uncertainty handling
Reverse logistics
Integrated design
Data models
Deterministic approach
ISSN:0278-6125, 1878-6642
Online Access:Get full text
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Summary:In this paper, we develop a stochastic programming model for an integrated forward/reverse logistics network design under uncertainty. First, an efficient deterministic mixed integer linear programming model is developed for integrated logistics network design to avoid the sub-optimality caused by the separate design of the forward and reverse networks. Then the stochastic counterpart of the proposed MILP model is developed by using scenario-based stochastic approach. Numerical results show the power of the proposed stochastic model in handling data uncertainty.
ISSN:0278-6125
1878-6642
DOI:10.1016/j.jmsy.2010.05.001