2016 INFORMS Annual Meeting Program

WE07

INFORMS Nashville – 2016

WE07 102B-MCC Data Mining in Decision Analytics Sponsored: Data Mining Sponsored Session Chair: Roy Jafari Marandi, Mississippi State University, MD, United States, rj746@msstate.edu 1 - Next-generation Sequencing (NGS) Data Analysis: Developing A Scalable Framework For The Future Michael Chuang, State University of New York, New Paltz, NY, 12601, United States, mikeychuang@gmail.com NGS analysis presents a domain for biomedical and information technology professionals to explore. Due to the large amount of data involved and various constraints of technologies, we delineate issues to consider to develop a framework using parallel computing and NoSQL database service to greatly reduce the required time under less infrastructure investments while achieving satisfactory accuracy. 2 - The Magnificent 7- The Killer Data Mining Errors Samuel Koslowsky, Senior Analytic Consultant, Harte Hanks, 2118 Ave T, Brooklyn, NY, 11229, United States, sam.koslowsky@hartehanks.com Most managers agree that data mining plays a critical role in assuring a successful marketing campaign. At times, errors can creep in. While analytic and technical errors can certainly harm a data mining exercise, most of the problems that emerge in a modeling project have little to do with technical issues. Rather, basic reasoning, and marketing related issues are at fault. Errors emerge from all phases of an exercise. From establishing an appropriate objective, to allowing sufficient time for completion, to misinterpreting the results to deploying results incorrectly. A good data mining analysis requires qualified personnel, domain knowledge experts, analysts, and IT professionals. 3 - Estimating Distance Decay Functions For Arts & Culture Markets Young Woong Park, Technical Professor, Southern Methodist University, 6212 Bishop Blvd. Fincher 303, Dallas, TX, 75275, United States, ywpark@smu.edu, Glenn Voss Distance decay functions capture the effect of distance on interaction intensity. Unlike typical efforts that use distance as a sole independent variable, we estimate a model that uses organizational, market, and demographic characteristics to explain variance across geographic markets. We build the model using transaction data for 7M HHs in 6 geographic markets and investigate characteristics predicting decay function shape and market-level differences. The resulting model can estimate decay functions in the absence of interaction intensity data. 4 - Self Organizing And Error Driven (SOED) Artificial Neural Network For Smarter Classifications Ruholla Jafari Marandi, Research Assistant, Mississippi State University, Starkville, MS, 39759, United States, rj746@msstate.edu, Mojtaba Khanzadeh, Brian Smith, Linkan Bian Albeit Artificial Neural networks’ high prediction power, the technique suffers from drawbacks such as intransparency. In this paper, motivated by learning styles in human brains, ANN’s shortcomings have been assuaged and, its prediction power has also been improved. Self-Organizing Map and Feedforward ANN are hybridized to solidify their benefits and help remove their limitations. The proposed method, which we have named Self-Organizing Error-Driven (SOED) Artificial Neural network, showed significant improvements in comparison with usual ANNs. Through experiencing 5 different datasets, we showed SOED is a more accurate, more reliable and more transparent technique. WE08 103A-MCC Improving Electricity Grid Flexibility Under Uncertainty Sponsored: Energy, Natural Res & the Environment, Energy I Electricity Sponsored Session Chair: Feng Qiu, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL, 60439, United States, fqiu@anl.gov 1 - Enhancing Flexibility Of Power Systems With Intelligent Periphery Yunhe Hou, University of Hong Kong, yhhou@eee.hku.hk Flexibility is a critical prerequisite for accommodating large-scale variable renewables before a clean, efficient, reliable, resilient, and responsive smart grid

can be established. In this talk, the metrics for assessing flexibility of the systems with large-scale renewable integration will be discussed first. Second, a method for enhancing flexibility, entitled risk-limiting dispatch, will be introduced. Finally, the operating strategies of intelligent periphery with electric springs will be discussed as a powerful tool to enhance flexibility of systems. 2 - Robust Defense Strategy For Gas-electric Systems Against Malicious Attacks Cheng Wang, Tsinghua University, Beijing, China, wangcheng525525@gmail.com, Wei Wei, Jianhui Wang, Feng Liu, Feng Qiu, Shengwei Mei This talk proposes a methodology to identify and protect vulnerable components of connected gas and electric infrastructures from malicious attacks, and to guarantee a resilient and flexible operation by deploying valid corrective actions (while accounting for the interdependency of gas pipeline network and power transmission network). The proposed mathematical formulation reduces to a tri- level optimization problem. By reformulating the lower level problem as a mixed integer linear programming , a nested column-and-constraint generation algorithm is developed to solve the min-max-min model. Case studies demonstrate the effectiveness and efficiency of the proposed methodology. 3 - A Study Of Ramp Management And Its Compensation Schemes Dane Andrew Schiro, ISO New England, Holyoke, MA, United States, dschiro@iso-ne.com, Eugene Litvinov, Tongxin Zheng, Feng Zhao The integration of renewable generation could make it more difficult for U.S. ISOs to satisfy real-time power balance constraints. This talk will summarize the existing power balance issue, present the current solution of ISO New England, and explore two potentially better solutions: ramp products and multi-period market clearing. Formulations of these new methods will be presented along with discussions of their foreseeable issues. It is hoped that this talk will encourage rigorous investigation into these emerging ideas, thus aiding in future ISO market improvements. 4 - Provide Ramping Service With Wind To Enhance Power System Operational Flexibility Qin Wang, National Renewable Energy Laboratory (NREL), Golden, CO, United States, qin.wang@nrel.gov, Bri-Mathias Hodge Maintaining the power system balance requires controllable resources to adjust their power output to match the time-varying net load. This is becoming more challenging when the proportion of generation from variable and uncertain renewable resources in the system is high. This presentation will demonstrate the feasibility and approaches to rely on wind power to provide ramping service in the electricity markets. Advanced wind ramp forecasting methodologies are discussed. In addition, methods on how to quantify power system flexibility enhancement by using wind power to provide ramping service will be presented. WE09 103B-MCC Logistics of Biomass Feedstock for Liquid Fuel Production Sponsored: Energy, Natural Res & the Environment I Environment & Sustainability Sponsored Session Chair: Daniela Gonzales, Texas A & M University, 3014 Jennifer Drive, College Station, TX, 77845, United States, danielasofiagonzales@gmail.com 1 - A Two-Stage Chance-constrained Stochastic Programming Model For a Bio-fuel Supply Chain Network With Uncertain Biomass Supply Md Abdul Quddus, PhD Student, Mississippi State University, Department of Industrial & Systems Engineering, PO Box 9542, Starkville, MS, 39762, United States, mq90@msstate.edu, Sudipta Chowdhury, Mohammad Marufuzzaman This study presents a two-stage chance-constrained stochastic programming model that captures the uncertainties due to feedstock seasonality in a bio-fuel supply chain network. The chance constraint ensures that, with a high probability, Municipal Solid Waste (MSW) will be utilized for bio-fuel production. To solve our proposed optimization model, we use a combined sample average approximation algorithm which is made faster by using star-inequalities. We use the state of Mississippi as a test bed to visualize and validate the modeling results. Our computational experiments reveal some insightful results about the impact of MSW utilization on a bio-fuel supply chain network performance.

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