Inventory-based Temporal Modeling for Freight Networks.

摘要

Freight transportation demand is a highly variable process over time and space. Two challenges in current regional freight forecasting are the lack of consideration of the space-time trade-offs and the lack of behaviorally-based models for temporally assigning annual commodity flows to daily flows. State-of-the-practice models typically use fixed factors for temporal assignment and do not address the tradeoffs between transport costs and inventory costs, which can aid in quantifying the impact of different land uses on monthly truck distributions or the impact of rising fuel costs on shipment frequency and warehousing needs. This dissertation work makes the first step toward explicitly modeling the freight temporal distributions and proposes a novel approach that adopts the concept of Network Economics and Economic Order Quantity (EOQ) inventory in an agent-based freight demand modeling framework.;Unlike other agent-based models that seek to replace the whole freight forecasting process, the proposed model relies on other aggregate models to generate annual distribution channels (commodity OD matrix) and monthly demand distributions by commodity type. This frees the model to focus on trade-offs between transport and inventory without having to bear the burden of limited disaggregate data for other choices.;The modeling framework is composed of two main components: (1) a supplier selection module to indicate the supply chain interactions and determine the order quantity from one firm to another firm while meeting the zone level flow constraints; (2) an EOQ-based inventory operation module to indicate the goods movement daily pattern and determine the daily firm-firm flows by modeling firms' inventory replenishment decisions. By aggregating the daily firm-firm flows back up to the zone level, we get the average zone-zone daily flows by commodity types as the final output.;The whole framework has been fully examined using the California data. A union of 6 datasets is utilized as inputs to model the daily flows of 503 firm groups in California during the 261 weekdays in year 2007. As one parameter of the normative model, the unit inventory holding cost has been calibrated with the given inventory data. A simple comparison of the model outputs with the fixed factor approach is conducted. Four use cases are presented to demonstrate the effectiveness of such a new model for freight transport analysis.