نتایج جستجو برای: transportation demand

تعداد نتایج: 199160  

سجاد مرادی, , سید هادی ناصری, , نعمت الله تقی نژاد, ,

Pipeline as a safe and economic way, play an important role in the oil transportation. In this system, various type of products are injected into the pipeline sequentially without any physical separation, and on the other side, at the distribution centers, the products are received and depot in the corresponding tanks. Scheduling of oil transportation operations in a given time horizon is an ma...

2007
Kurt Jörnsten

This paper deals with the so-called transportation problem of linear stochastic fractional programming, and emphasizes the wide applicability of LSFP. The transportation problem, received this name because many of its applications involve in determining how to optimally transport goods. However, some of its applications (e.g., production scheduling) actually have nothing to do with transportati...

H. Soleimani, M. Seyyed Esfahani N. Shirazi

This paper considers a three-stage fixed charge transportation problem regarding stochastic demand and price. The objective of the problem is to maximize the profit for supplying demands. Three kinds of costs are presented here: variable costs that are related to amount of transportation cost between a source and a destination. Fixed charge exists whenever there is a transfer from a source to a...

2007
Philippe A. Bonnefoy

With the growing demand for air transportation and the limited ability to increase capacity at key points in the air transportation system, there are concerns that, in the future, the system will not scale to meet demand. This situation will result in the generation and the propagation of delays throughout the system, impacting passengers’ quality of travel and more broadly the economy. There i...

Journal: :Transactions of the Japan Society of Civil Engineers 1967

Journal: :Proceedings of the ... AAAI Conference on Artificial Intelligence 2021

Graph Convolutional Network (GCN) has been widely applied in transportation demand prediction due to its excellent ability capture non-Euclidean spatial dependence among station-level or regional demands. However, most of the existing research, graph convolution was implemented on a heuristically generated adjacency matrix, which could neither reflect real relationships stations accurately, nor...

Journal: :IOP Conference Series: Earth and Environmental Science 2019

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید