Performance Optimization of Multi-Criteria Route Planning Algorithms: A Case Study in HAZMAT Emergency Response

This study investigates the multi-criteria route optimization problem within complex urban expressway networks. The primary objective is to develop and evaluate a novel pathfinding approach by integrating a Delphi-AHP-weighted cost function into the A* algorithm, thereby dynamically balancing operational efficiency and public safety. By employing the Delphi Technique with a panel of 17 experts, a specialized cost function was derived that incorporates twelve critical parameters, including traffic fluidity, population density, and chemical dispersion metrics modeled via ALOHA. This re-search applied the proposed model to a high-stakes hazardous material (HAZMAT) emergency response scenario to benchmark its performance against established base-lines, specifically Dijkstra’s algorithm and Ant Colony Optimization (ACO). Simulation results demonstrate that the Delphi-weighted A* algorithm achieves an approximately 3.8 % reduction in travel time relative to Dijkstra’s algorithm while enhancing safety scores by approximately 8.6%. These findings provide a robust framework for algo-rithmic decision-support in time-critical logistics and infrastructure management.