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Fuzzy Sets and Systems
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Integrated multistage logistics network design by using hybrid evolutionary algorithm
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Computers and Industrial Engineering
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Fuzzy Sets and Systems
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Computers and Operations Research
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AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 01
A stochastic model for forward-reverse logistics network design under risk
Computers and Industrial Engineering
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Measuring and controlling emissions across the logistics network is an important challenge for today's firms according to increasing concern about the environmental impact of business activities. This paper proposes a bi-objective credibility-based fuzzy mathematical programming model for designing the strategic configuration of a green logistics network under uncertain conditions. The model aims to minimize the environmental impacts and the total costs of network establishment simultaneously for the sake of providing a sensible balance between them. A popular but credible environmental impact assessment index, i.e., CO"2 equivalent index is used to model the environmental impact across the concerned logistics network. Since transportation mode and production technology play important roles on the concerned objectives, the proposed model integrates their respective decisions with those of strategic network design ones. In addition, to solve the proposed bi-objective fuzzy optimization model, an interactive fuzzy solution approach based upon credibility measure is developed. An industrial case study is also provided to show the applicability of the proposed model as well as the usefulness of its solution method.