Warren B. Powell, Pierre Humblet. / "June 1985." "EES-83-5" "Revised May, 1985" / Bibliography: p. 22. / "Research supported by NSF under grant No.CEE-8203476." "... partial support provided lby NSF under grant No. NSF-ECS-8310698."

With congestion, environmental Impact, and the price of oil becoming topics that influence businesses and individuals in a daily basis, measures need to be undertaken in order to accommodate the growing demand for freight transportation. By directing many of the trucks travelling along the National Highways Systems to the Marine Highway corridors developed by the U.S. Maritime Administrations, many of the problems can be addressed in the Short and Medium terms. In order to do so, Short Sea Shipping, through the use of Ro/Ro (Roll-on/Roll-off) Vessels, needs to be implemented. Although the environmental and congestion reducing benefits are considerable, the profitability of this transportation mode needs to be considered. A cost benefit analysis can determine the margin of profit, and attract investors and businesses. By developing a mathematical model that accounts the costs associated with transporting trucks along a particular corridor, the competitiveness of Short Sea Shipping can be determined. / by Alvaro Galletebeitia. / Thesis (M.S.C.S.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

Please read the abstract in the section 00front of this document / Dissertation (MSc (Industrial Systems))--University of Pretoria, 2006. / Industrial and Systems Engineering / unrestricted

This research addresses fleet-sizing for reusable containers that are used for protection, transportation, and storage of parts between a component plant and assembly plant. These reusable containers are often expensive and occupy a large amount of storage space when empty and full. Having a large container fleet comes with higher acquisition, maintenance, and storage costs, but decreases production down time caused by the lack of containers needed for storage. A quantitative model of these trade-offs will permit decision makers to maintain desired production levels at minimum cost. In this dissertation, the relationship between container fleet size and production down time caused by container shortages is researched. Utilizing both theoretical and empirical approaches, two analytical models that include relevant operational parameters and stochastic components are developed. The first is a container fleet sizing model, and the second model estimates production stoppages as a function of container fleet size. The formulas are shown to be accurate and provide decision makers with the tools to better plan and manage specific applications. The formulas also provide general insight into the factors that affect container fleet size and production stoppage due to container shortages. / Graduation date: 2012

A load plan specifies how freight is routed through a linehaul terminal network operated by a less-than-truckload (LTL) carrier. Determining the design of the load plan is critical to effective operations of such carriers. This dissertation makes contributions in modeling and algorithm design for three problems in LTL load plan design: (1) Refined execution cost estimation. Existing load plan design models use approximations that ignore important facts such as the nonlinearity of transportation costs with respect to the number of trailers, and empty travel beyond what is required for trailer balance that results from driver rules. We develop models that more accurately capture key operations of LTL carriers and produce accurate operational execution costs estimates; (2) Dynamic load planning. Load plans are traditionally revised infrequently by LTL carriers due to the difficulty of solving the associated optimization problem. Technological advances have now enabled carriers to consider daily load plan updates. We develop technologies that efficiently and effectively adjust a nominal load plan for a given day based on the actual freight to be served by the carrier. We present an integer programming based local search procedure, and a greedy randomized adaptive search heuristic; and (3) Stochastic load plan design. Load plan design models commonly represent origin-destination freight volumes using average demands, which do not describe freight volume fluctuations. We investigate load plan design models that explicitly utilize information on freight volume uncertainty and design load plans that most cost-effectively deal with varying freight volumes and lead to the lowest expected cost. We present a Sample Average Approximation approach and a variant of the method for solving the stochastic integer programming formulations.