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 through matching 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.
