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Congestion Reduction Through Efficient Empty Container Movement Under Stochastic Demand

Maged Dessouky, Santiago Carvajal and Siyuan Yao

Institute of Transportation Studies, Working Paper Series from Institute of Transportation Studies, UC Davis

Abstract: In today’s world, there is a significant amount of investigation regarding how to efficiently distribute loaded containers from the ports to the consignees. However, to fully maximize the process and become more environmentally friendly, one should also study how to allocate the empty containers created by these consignees. This is an essential part in the study of container movement since it balances out the load flow at each location. The problem of coordinating the container movement to reuse empty containers and lower truck miles is called the “Empty Container Problem”. In this work, the authors develop a scheduling assignment for loaded and empty containers that builds on earlier models but incorporates stochastic (random) future demand. Since this problem is meant to be solved daily and the solution implemented today affects tomorrow’s starting state, incorporating future demand is an important aspect. This report shows that the truck miles needed to satisfy the demand at all locations is reduced by about 4-7% when considering future stochastic demand as opposed to only considering today’s demand. Thus, leading to a cleaner and greener solution, creating less congestion and lowering the impact of freight movement on the environment. View the NCST Project Webpage

Keywords: Engineering; Containers; Demand; Empty car miles; Freight handling; Mathematical models; Routing; Scheduling; Stochastic processes; Traffic assignment; Trucks (search for similar items in EconPapers)
Date: 2020-06-01
New Economics Papers: this item is included in nep-tre
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