It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
As freight transportation demand increases worldwide, railway practitioners must carefully manage the capacity of existing facilities to ensure efficient and reliable operations. Railroad gravity hump classification (marshalling) yards, where individual railcars (wagons) are sorted into new trains to reach their destination, are an integral part of the freight rail network. Efficient operation of yard processes is critical to overall freight railway performance as individual carload shipments moving in manifest trains spend most of their transit time waiting for connections at intermediate yards, with more than half of this waiting time spent dwelling on classification bowl tracks. Previous research has developed optimal strategies to allocate bowl tracks to blocks for a given set of yard track lengths. However, these strategies make simple assumptions about the performance impact of over-length blocks due to a lack of basic analytical models to describe this relationship. To meet this need, this paper develops an original hump classification yard model using AnyLogic simulation software. A representative yard with accurate geometry and operating parameters reflecting real-world practice is constructed using AutoCAD and exported to AnyLogic. The AnyLogic discrete-event simulation model uses custom Java code to determine traffic flows and railcar movements in the yard, and output performance metrics. With complete flexibility to change track layout patterns, a series of simulation experiments quantify fundamental classification yard capacity relationships between performance metrics and the distribution of track lengths, as a function of the railcar throughput volume and size of outbound blocks created in the yard. The resulting relationships are expected to better inform railway yard operating strategies as traffic, train length, and block size increase but yard track lengths remain static.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer