If you are simulating the movement of trains, the operation of railway junctions, or rail systems in general, we recommend watching our Rail Library webinar.
The webinar focuses on the specialized AnyLogic library for modeling and simulating rail operations. Presented by SimulAi, AnyLogic’s UK partner, the webinar gives an overview of the Rail Library, provides industrial case studies, and explores new AI possibilities.
Rail Library webinar video, a step-by-step guide to rail network modeling, highlighting features useful for your next rail modeling projects.
You can also download the materials from the webinar. The model and shape files are included, allowing you to explore the example yourself, or follow the recording in the video at your own pace. Write-ups of both the model-building and the insightful Q & A session are also included.
Tue, Oct 10, 2017 - Join us for a webinar featuring the Rail Library, one of AnyLogic’s industry-specific libraries.
AnyLogic’s Rail Library allows you to efficiently model, simulate and visualize rail yard and rail transportation operations of any complexity and scale.
The webinar will detail how to build a railway network, including yards, and highlight features useful for your future rail modeling projects.
The Handbook of Operations Research Applications at Railroads (International Series in Operations Research & Management Science) is the first book to offer a complete spectrum of the role that operations research has played and can play in the improvement of North American freight railroads. It explores how decisions are made at railroads, contains examples of the mathematical programming formulations to the complex problems, and provides insights into real-world applications. AnyLogic is featured in two chapters: Simulation of Line of Road Operations and Terminal Simulation written by Roger Baugher, who has worked to apply Operations Research tools to railroads for over 40 years as both a railroad employee and consultant (B. Patty, Preface). Roger was instrumental in the development of Algorithmic Blocking and Classification (ABC) while at Norfolk Southern, was the first recipient of the Railroad Applications Special Interest Group (RASIG) Award for his contributions to OR in the railroad industry and is a Franz Edelman Laureate. In addition to Norfolk Southern, Roger Baugher applied his understanding of network optimization approaches to various forms of the transportation organizations, such as BNSF, American Airlines, Pacer Stacktrain, Conrail where he played an integral part in developing the Conrail Network Analysis Model (CNAM)
Transportation of hazardous materials, notably crude oil by rail are increasing in Canada and the USA. Due to the July 2013 Lac Megantic Train Derailment Disaster and increased concerns raised by municipalities across the country, Canadian Government issued a “protective direction” that requires railway companies to share dangerous goods data with municipalities and first responders. Ali Asgary, Associate Professor, Disaster & Emergency Management at York University in Toronto, Canada is an expert in disaster, emergency, and business continuity management. His extensive research and effective teaching are enhanced by his active contributions to the profession and by translating them into real world practices at different levels. Dr. Asgary selected AnyLogic due to it’s multimethod, agent based and GIS capabilities to analyze and address the situation.
Over ninety percent of the world’s trade containerized, and in the Port of Hamburg in Germany over nine million containers are transshipped every year. Till now the early provision of information for both the estimated time of arrival (ETA) of vessels and containers is not established. Containers are offloaded and stored at terminals, and then they are usually sent by ground transportation to their further destinations. This hinterland part of the supply chain can often become a bottleneck because if a deep-sea vessel gets delayed, it can complicate further shipment processes. Furthermore, the terminal has no information about the hinterland mode selected or the time of off-loading a certain container (first or last).
While the extensive rail library was a key reason that CSX chose AnyLogic as its general purpose simulation tool for the Network Modeling, Operations Research, and Process Excellence groups, the other libraries and methods have added significant value as well. In fact, the first major project where AnyLogic was used did not utilize the rail library. After reviewing the problem in more detail, a discrete-event simulation model was built to help managers studying train throughput. The model simulated the demand of empty trains from five coal mines, as well as the fulfillment of the demand. A supply-chain-like network model was created, which implemented logic to depict the demand, supply and staging of empty trains. The trains were modeled as moving entities across the network. By varying values of relevant parameters, users can infer the impacts of different factors to the train throughput (i.e. siding staging capacity and loading speeds at the coal mines). The model provides a way for decision makers to gain insight into the system to help identify the maximum possible throughput. The objective was to identify the best operational/capital strategy to handle the increased business.
The sphere of public transportation services in Australia is undergoing a transformation in response to a number of drivers, such as a need for inter-modal integration and widespread introduction of consumer information technologies. However, in order to better address new challenges associated with these changes one must first develop an understanding of the dynamic relationships between the way public transportation system operates and the many ways in which people use it to achieve desired mobility. The public transportation company employed PwC to develop a solution for better decision-making and problem-solving. A model was built using AnyLogic 7 as a platform to unify and animate various static data into a dynamic system of interactions. The model is based on three sources of information: network structure provided in GIS format, service timetable in tabular form and ticket sales information gathered from a variety of systems.
