Fan Peng is a Ph.D. candidate in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign (UIUC). He received his B.S. degree in Civil Engineering from Tsinghua University, China, in 2007, and his M.S. degree in Civil and Environmental Engineering from UIUC in 2008. He expects to complete his Ph.D. degree in Civil and Environmental Engineering from UIUC in 2011. As a graduate student, he has been working with Prof. Yanfeng Ouyang on a range of large-scale combinatorial optimization problems in the fields of transportation operations, management and planning. In particular, he has been collaborating with CSX Transportation, both as a UIUC research assistant over the past two and a half years, and as a summer intern at their Jacksonville headquarters in 2010, on several railroad scheduling and planning problems.
U.S. Class 1 railroads spend billions of dollars annually on track maintenance in order to ensure the safety and operational efficiency of their networks. Efficient planning the use of their extensive maintenance resources across these large networks is a complex problem with major cost implications. Currently, the decision-making process for track maintenance planning is largely manual, relying primarily on the knowledge and expert judgment of planning personnel. Use of operations research techniques to develop solutions to such problems offers opportunities to improve the process, especially in light of the rapid retirement of experienced railroad personnel. Consequently, CSX Transportation has been supporting research at the University of Illinois developing mathematical models and solution algorithms for optimization problems on track maintenance. Several of these approaches have already been implemented by CSX to assist their experts in the planning process. This seminar will present two of the optimization problems that have been studied: track inspection scheduling and production team scheduling.
Track inspection scheduling involves multiple inspection teams traveling over various portions of the network to identify track defects. This is a large-scale routing and scheduling problem in which thousands of inspection activities are to be scheduled subject to many difficult side constraints such as periodicity and discrete work time constraints. A vehicle routing problem formulation and a customized algorithm were developed to efficiently solve the problem. Production team scheduling involves track maintenance capital projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. The algorithm schedules projects to minimize travel costs of all the production teams while satisfying many types of side constraints including complex mutual exclusion and consecution constraints. A multiple neighborhood search algorithm and various performance enhancement techniques were developed to efficiently solve the proposed time-space network model.
The strategies each of these four countries undertook to develop their high-speed rail industry are a good reference for future development of high-speed rail elsewhere. The technical lessons learned will be beneficial to the planning, design and construction in North America and these topics this will be the subject of this presentation.