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Stochastic freight flow patterns: implications for fleet optimization
Affiliation:1. Faculty of Finance, Cass Business School, City University London, 106 Bunhill Row, London EC1Y 8TZ, United Kingdom;2. Department of Accounting, Finance and Governance, Westminster Business School, University of Westminster, 35 Marylebone Road, London NW1 5LS, United Kingdom
Abstract:Trucking, rail and other types of transportation networks share the common feature of moving equipment and crews between spatially separated terminals to accommodate the transportation of goods or people. This paper develops measures for temporal and spatial imbalances in freight flows, and applies these measures to a major trucking network. Fundamentally, the randomness inherent to a system of terminals is mitigated by pooling freight flows among terminal groups, and by pooling freight flows over many time periods. In the terminal network that we examined, long-run freight imbalances ensure that empty equipment movements must equal or exceed 13.3% of loaded movements at individual terminals and 8.2% of loaded movements at terminal groups. Due to short-run freight imbalances, the number of empty movements could increase by about 50% over the long-run average; greater increases would occur if equipment flows must be balanced on each travel lane. ©
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