Wipaporn Kitthiphovanonth, Chalermchai Chaikittiporn, Arroon Ketsakorn, Korn Puangnak
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 cost function weighted by the Delphi-Analytic Hierarchy Process (AHP) 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 Areal Location of Hazardous Atmosphere (ALOHA) This research applied the proposed model to a high-stakes Hazardous Material (HAZMAT) emergency response scenario to benchmark its performance against established baselines, 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 expert-validated safety scores (a weighted metric of risk factors including population density and chemical dispersion) by approximately 8.6%. These findings provide a robust framework for algorithmic decision-support in time-critical logistics and infrastructure management. While numerically modest, these improvements are critical in HAZMAT scenarios, where even marginal time savings directly support the ‘Golden Hour’ principle and minor route adjustments can prevent catastrophic secondary exposure.