A novel optimization method for hazardous materials vehicle routing with temperature-based time windows

Area of Science:

• Operations Research
• Logistics Management
• Environmental Science

Background:

• The sharing economy has led to the rise of shared intermediate bulk containers (IBCs).
• High temperatures significantly impact the optimal routing of vehicles transporting hazardous materials (hazmat).
• Existing routing models often do not account for temperature-dependent constraints.

Purpose of the Study:

• To propose a variant of the hazmat vehicle routing problem that integrates shared IBCs.
• To develop a refined mixed non-linear integer programming model considering temperature-based time windows.
• To introduce a novel adaptive large neighborhood search (ALNS) algorithm for solving this problem.

Main Methods:

• Formulation of a mixed non-linear integer programming model.
• Integration of temperature-based time windows into the routing model.
• Development and application of a novel adaptive large neighborhood search (ALNS) algorithm with new heuristic operators.

Main Results:

• The proposed ALNS algorithm effectively solves the hazmat vehicle routing problem with shared IBCs and temperature-based time windows.
• Numerical examples using the Solomon set demonstrate the algorithm's suitability.
• Quantification and integration of temperature-based time windows were achieved.

Conclusions:

• The developed model and ALNS algorithm provide an effective solution for optimizing hazmat logistics with shared IBCs under varying temperatures.
• This research contributes to more efficient and safer transportation of hazardous materials.
• The findings highlight the importance of considering environmental factors in vehicle routing optimization.