Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations
Abdelrahman Ismael, Taner Cokyasar
TL;DR
The paper tackles data limitations in freight modeling by developing a calibrated, large-scale agent-based model that integrates supplier selection and commodity assignment within POLARIS-Freight. It introduces a two-phase optimization framework (supplier selection followed by commodity assignment) and a probabilistic international importer/exporter heuristic, calibrated to match regional FAF/CFS flows and shipping distance distributions. The model is implemented across four U.S. metros (Atlanta, Chicago, DFW, LA) and demonstrates high fidelity in reproducing observed freight patterns, while revealing region-specific trade structures and resilience implications. This framework enables policymakers and planners to evaluate infrastructure investments and disruption-response strategies with a detailed, micro-level view of supplier–receiver interactions and their network-wide effects.
Abstract
Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and supplier rating model adapted from existing literature. The model's core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas, Atlanta, Chicago, Dallas-Fort Worth, and Los Angeles, the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision-making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.