Abstract:Rural roads represent an important part of the economy in the Great Plains and Midwest of the United States. As oil exploration in North Dakota increases, the number of vehicles travelling on these roads is also increasing, resulting in significant needs for infrastructure maintenance and upgrades, including the construction of new bridges. The lifecycle benefit-cost analysis of bridge construction is the overall objective of this research. This paper investigates the benefits of combining travel demand modeling and lifecycle benefit-cost analysis, and demonstrates traffic forecasting using geographic information systems (GIS) and network flow problem. The paper also shows a comparison of the alternative scenarios. The authors demonstrate a method of integrating geographic information systems, operations research, and data analytics to estimate future traffic by evaluating infrastructure needs. The travel demand modeling is essential for the lifecycle benefit-cost analysis. This study would help government agencies and construction companies evaluate and prioritize new bridge construction projects. The agencies should consider adding the environmental costs.
The sugar beet is one of the most important crops for both social and economic reasons, even though the area under sugar beet cultivation in the Red River valley of North Dakota and Minnesota is comparatively smaller that of corn and other crop lands. It generates a large economic activity in local and regional level with a greater impact on jobs and stimulation of agriculture, transportation, and farm economy. Sugar beet transportation takes place in two stages in Red River Valley: the first step is from farms to piling centers (pilers) and the second step from pilers to processing facilities. This study focuses on the problem of optimizing piler locations based on supply variation. Sugar beet supply and harvest varies significantly due to numerous reasons such as weather, water availability, and different maturity dates for the crop. This provides for a variable optimal harvesting time based on the plant maturity and sugar content. Sub-optimized pilers location result in the high transportation and utilization costs. The objective of this study is to minimize the sum of transportation costs to and from pilers and the pilers utilization cost. A two-step algorithm based on the geographical information system (GIS) with global optimization method is used to solve this problem. This method will also be useful for infrastructure decision makers such as planners and engineers to predict the truck volume on rural roads.
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