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Resolution of an uncertain closed-loop logistics model: an application to fuzzy linear programs with risk analysis
1Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan, ROC. hfwang@ie.nthu.edu.tw
Journal of Environmental Management
|June 16, 2010
Summary
This study introduces a generalized fuzzy model for green logistics, addressing uncertainty in global warming mitigation. It offers a decision-making framework balancing logistic costs against potential resource constraint violations.
Area of Science:
- Environmental Science
- Operations Research
- Supply Chain Management
Background:
- Global warming necessitates green supply chain management, with a focus on logistics.
- Existing closed-loop green logistics models often overlook general environmental uncertainty.
- Fuzzy numbers are introduced to model uncertainty in green logistics.
Purpose of the Study:
- To propose a generalized green logistics model incorporating uncertainty using fuzzy numbers.
- To develop an interval programming model to handle fuzzy data in logistics.
- To provide a decision-making mechanism for balancing cost and risk.
Main Methods:
- Utilizing fuzzy numbers to represent uncertainty in the logistics environment.
- Developing an interval programming model based on means and imprecision indices.
- Integrating fuzzy number level cuts for comprehensive uncertainty analysis.
- Resolving the interval programming model based on decision-maker preferences.
Main Results:
- The proposed model provides solutions with a confidence level, including risk assessment.
- Increased decision-maker optimism leads to better solutions but higher constraint violation risk.
- A trade-off mechanism between logistic costs and risk is established.
- Numerical illustrations demonstrate the practical application of the solution procedure.
Conclusions:
- The fuzzy-based interval programming model effectively handles uncertainty in green logistics.
- Decision-makers can optimize logistics by understanding the trade-off between cost and risk.
- The model supports informed decision-making in environmentally conscious supply chain management.
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