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Mathematical Problems in Engineering
Volume 2013, Article ID 823876, 10 pages
Research Article

A Multiobjective Optimization Model in Automotive Supply Chain Networks

1Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, University Putra Malaysia, 43400 Serdang, Selangor, Malaysia
2Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

Received 5 February 2013; Revised 10 June 2013; Accepted 5 August 2013

Academic Editor: Bijaya Panigrahi

Copyright © 2013 Abdolhossein Sadrnia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In the new decade, green investment decisions are attracting more interest in design supply chains due to the hidden economic benefits and environmental legislative barriers. In this paper, a supply chain network design problem with both economic and environmental concerns is presented. Therefore, a multiobjective optimization model that captures the trade-off between the total logistics cost and CO2 emissions is proposed. With regard to the complexity of logistic networks, a new multiobjective swarm intelligence algorithm known as a multiobjective Gravitational search algorithm (MOGSA) has been implemented for solving the proposed mathematical model. To evaluate the effectiveness of the model, a comprehensive set of numerical experiments is explained. The results obtained show that the proposed model can be applied as an effective tool in strategic planning for optimizing cost and CO2 emissions in an environmentally friendly automotive supply chain.