Abstract

This paper presents a methodology for determining the optimal supply chain design with economic, environmental and risk management considerations. A multi-objective model based on mixed integer programming is proposed seeking three objectives: First, to minimize the total cost of transportation and the costs associated to the use of intermediate nodes. Second, to minimize the risks of product losses in transportation. Third, to minimize the environmental impact of CO2 emissions produced by transportation and storage operations. The proposed model is solved with two approaches: First, a commercial solver to compute the Pareto-optimal set of solutions. Second, a simulation-based optimization approach that allows to obtain statistically different but efficient solutions such that the decision-maker will be able to trade-off objectives while considering only Pareto optimal solutions. Experiments on random instances demonstrate the capability of the models and methods.

Details

Title
Simulation-optimization techniques for closed-loop supply chain design with multiple objectives
Author
Guerrero, William Javier; Sotelo-Cortés, Laura Andrea; Romero-Motta, Enrique
Pages
202-210
Section
Articles
Publication year
2018
Publication date
2018
Publisher
Universidad Nacional de Colombia
ISSN
00127353
e-ISSN
23462183
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2123691050
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.