A green supply chain network design model for enhancing competitiveness and sustainability of companies in high north arctic regions

To survive in today's competitive and ever-changing marketplace, companies need not only to engage in their products and/or services, but also to focus on the management of the whole supply chain. Effectively managing and balancing the profitability and interconnection of each player in the sup...

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Bibliographic Details
Main Authors: Yu, Hao, Solvang, Wei Deng, Chen, Chen
Format: Text
Language:English
Published: International Energy and Environment Foundation (IEEF) 2014
Subjects:
Online Access:https://hdl.handle.net/10037/10454
Description
Summary:To survive in today's competitive and ever-changing marketplace, companies need not only to engage in their products and/or services, but also to focus on the management of the whole supply chain. Effectively managing and balancing the profitability and interconnection of each player in the supply chain will improve the overall supply chain surplus as well as individual profit. However, it is extremely difficult to simultaneously optimize several objectives in design and planning of a supply chain, i.e., cost-minimization, risk-minimization, responsiveness-maximization, etc., which are somehow conflict with one another. Furthermore, the natural and infrastructural challenges in high north arctic regions make it become much more difficult and complicated to design and develop cost-efficient, highly responsive, environmentally friendly, and sustainable supply chain network. In order to provide companies in high north arctic regions with decision support tool for the design and planning of theirs supply chain networks, a green supply chain network design (GrSCND) model is formulated in this study based on multi-objective mixed integer programming (MIP). The optimal trade-off among several conflicting objectives is the focus of this GrSCND model aiming to enhance both competitive competence and sustainability of companies and supply chains operated in high north regions. In addition, a numerical experiment is also given to present a deep insight of the GrSCND model. Copyright © 2014 International Energy and Environment Foundation -All rights reserved.