Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming

Area of Science:

• Agricultural Economics
• Operations Research
• Sustainable Energy Systems

Background:

• Biofuel supply chains face significant uncertainties in resource availability, pricing, and market demand.
• Optimizing the life cycle cost of these supply chains is crucial for economic viability and sustainability.
• Existing models often struggle to account for the inherent variability in key parameters.

Purpose of the Study:

• To develop a comprehensive model for optimizing the life cycle cost of biofuel supply chains under uncertainty.
• To incorporate multiple agricultural zones, transportation modes, biofuel plants, and market centers.
• To address uncertainties in resource prices, grain yield, and market demands using interval numbers.

Main Methods:

• Developed an interval linear programming model to handle uncertain parameters.
• Presented a novel method for solving the developed interval linear programming problem.
• Utilized an illustrative case study to validate the model's applicability.

Main Results:

• The proposed model successfully optimized the life cycle cost of the biofuel supply chain.
• The model demonstrated feasibility in designing biofuel supply chains under various uncertainty scenarios.
• Results confirmed the effectiveness of interval linear programming in managing supply chain variability.

Conclusions:

• The developed interval linear programming model provides a robust framework for optimizing biofuel supply chain design under uncertainty.
• This approach enhances decision-making by accounting for the range of possible outcomes.
• The model is a valuable tool for ensuring the economic and operational efficiency of biofuel production and distribution.