Informs Annual Meeting 2017

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INFORMS Houston – 2017

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non-linear and non convex in the variables of interest. On the other hand, we are also interested in discrete optimization models where supply and demand closely interact, which is typically the case in transportation. Such models are associated with (mixed) integer optimization problems, whose discrete variables are used to design and configure the supply. The goal of this research is to develop a general methodology which integrates both supply and demand under the framework of discrete choice models whose associated mixed integer linear problems are scalable and solvable within reasonable time. 2 - Integrated Computational and Theoretical Scheme for Linking Quality Control and Stochastic Modeling in Bioenergy Supply Chain Network Design Krystel Castillo, University of Texas-San Antonio, San Antonio, TX, Contact: Krystel.Castillo@utsa.edu In recent years, industry has seen the advent of highly complex, large-scale supply chains (SCs), whichhave become increasingly difficult to analyze and optimize using conventional modeling techniques and solutionprocedures. A particularly relevant example is found in the emerging second-generation biofuel industry, whichfaces unique, unaddressed challenges such as: (1) understanding the biomass quality/availability and quantifying howthese variables impact the design of technologies, and (2) assessing the impact of uncertainties related to thebiomass quality/availability on the supply chain design and planning. This presentation will include a discussion on a unified computational and theoretical scheme that links qualitycontrol, twostage stochastic modeling and tractable optimization algorithms to (1) enable the conversion of largequantities of biomass into marketable products, (2) better represent the random nature of the biomass quality, and (3)assess the impact of these uncertainties on the system’s design. These computational tools are being integrated into science-as-service platform. This alpha version of a cloud-based Decision Support System aims to facilitate the adoption of experimental and field data as well as computational models.. 370C Big Data and Institutional Research Sponsored: INFORMS Special Sessions Sponsored Session Chair: Grace Lin, Institute for Information Industry, 1F, No. 133, Sec. 4, Minsheng E. Rd., Taipei, na, Taiwan, gracelin.ny@gmail.com 1 - Big Data Analytics-Based Pricing and Revenue Management Roger Gung, University of Phoenix, Phoenix, AZ, roger.gung@phoenix.edu Using big data for better pricing is a critical strategy for revenue management. Nowadays commodity and service industries have been developing big data analytics-based pricing systems to optimize profit or return on investment. In this talk, we present a general methodology for pricing and revenue management using big data analytics. The methodology includes statistical models for predicting customer buying behavior and an optimization framework for optimizing profit or return on investment. The talk also presents a method to normalize variable impacts and rank the importance of the variables. 2 - An AI-based Framework for IR Decision-making Grace Lin, Institute for Information Industry, 1F, No. 133, Sec. 4, Minsheng E. Rd., Taipei, Taiwan, gracelin.ny@gmail.com, Jeffrey Tsai, Ya-Hui Chan, Jianian Cheng, Yang Tinying, Ct Lee In this talk, we will present a framework for a self-learning IR decision-making system that incorporates internal information from an institution as well as external big data information such as market and emerging technology trends and job market in order to bridge the gap between industry talent needs and university education. SB62

362F Joint Session RAS/Practice: Education Programs in OR/MS for Railways Sponsored: ORinformed Healthcare Policies Sponsored Session Chair: Steven Harrod, Technical University of Denmark, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark, stehar@dtu.dk 1 - Railway Education Programs at the Technical University of Denmark and Other European Universities, and Related Careers Steven Harrod, Technical University of Denmark, Room 132, Building 424, Kgs. Lyngby, 2800, Denmark, stehar@dtu.dk Railway agencies, infrastructure managers, and operators nearly all desire formal university education today. This presentation summarizes the education programs available in Europe and some of the typical career paths available at European railways. 2 - OR/MS Education in Railways in China Xy Yin, Beijing Jiaotong University, Beijing, China, xyyin@bjtu.edu.cn This paper introduces the development process of the theory of Operations Research and Management Science in the education of the railway transportation in Beijing Jiaotong University. Beijing Jiaotong University has been established for 120 years. The major of railway transportation management is the earliest major in the school, and the theory of Operations Research and Management Science has been adopted in the major-related courses, including the organization of train operation and the organization of railway freight transportation. Such theory makes teaching level improved, helps to train a large number of qualified staffs in the fields of China railway transportation management. 3 - Railway Operations Education at the University of Illinois at Urbana-champaign The Rail Transportation and Engineering Center (RailTEC) at the University of Illinois at Urbana-Champaign is home to the strongest academic program in railroad engineering of any university in North America, complimented by the largest and most diverse program of research on the topic. After many years of decline, railways have reemerged as an area of interest to North American academicians. This presentation will describe how RailTEC uses a combination of coursework, research, industry internships and international collaboration to meet the challenge of educating the next generation of railway operations and engineering professionals. 4 - OR Careers in Railways at BNSF Pooja Dewan, Chief Data Scientist, BNSF Railway, 2650 Lou Menk Drive, #2, Fort Worth, TX, 76131, United States, pooja.dewan@bnsf.com As one of the largest freight railroads in North America, BNSF moves goods and commodities that feed and clothe millions of people; help build roads and buildings; and provide a critical link that connects consumers with the global marketplace. Railroads carry more than 40 percent of freight in the U.S. by volume and provide the most fuel-and cost-efficient means for moving freight over land. Behind the scenes helping equip BNSF leaders with the research necessary to make decisions on is the company’s Operations Research team. The team’s mission is to leverage advanced analytics to provide innovative tools and insights that help support and enhance the decisions made by company’s leaders. C. Tyler Dick, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, United States, ctdick@illinois.edu

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370B MIF Early Career Award Sponsored: Minority Issues Sponsored Session

Chair: Julie Simmons Ivy, North Carolina State University, North Carolina State University, Raleigh, NC, 27695-7906, United States, jsivy@ncsu.edu 1 - Choice-based Optimization in Transport, Mobility and Logistics Shadi Sharif Azadeh, Erasmus University Rotterdam, Rotterdam, Netherlands. Contact: sharifazadeh@ese.eur.nl Combining customer behaviour models in optimization provides a better understanding of the preferences of clients to policy makers while planning for their systems. These preferences are formalized with discrete choice models. However, their complexity leads to mathematical formulations that are highly

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