2015 Informs Annual Meeting

POSTER SESSION

INFORMS Philadelphia – 2015

7 - Intersection of a Tree Network for the Single Refueling Station Location Problem Sang Jin Kweon, PhD Student, The Pennsylvania State University, 310 Leonhard Building, State College, PA, 16802, United States of America, svk5333@psu.edu An intersection is the vertex whose degree is greater than two in the network. In this talk, we consider intersections and develops the methodology that determines the continuous interval of the potential locations for a single alternative-fuel refueling station on a tree network, with an objective of maximizing the amount Alireza Farasat, University at Buffalo (SUNY), 4433 Chestnut Ridge Rd Apt. 7, Amherst, NY, 14228, United States of America, afarasat@buffalo.edu, Alexander Nikolaev Educational systems have witnessed a substantial transition from traditional educational methods mainly using text books, lectures, etc. to newly developed systems which are artificial intelligent-based systems and personally tailored to the learners. We have developed a web-based tool, Crowdlearning which concentrates on creating an intelligent system that learns to interact with students and motivates them to more actively participate in the learning process by proposing their own problems. 9 - Optimized Scheduling of Sequential Resource Allocation Systems Ran Li, PhD Student, Georgia Institute of Technology, 755 Ferst Drive NW, Atlanta, GA, 30332, United States of America, rli63@gatech.edu, Spyros Reveliotis We consider the scheduling problem of allocating finite reusable resources to concurrent sequential processes. This problem also involves the logical issue of deadlock avoidance. Our approach is based on the formal model of the generalized stochastic Petri-net. Special emphasis is placed on the representational and computational complexity of the proposed methods, which are controlled through (i) a pertinent (re-)definition of the target policy spaces, and (ii) simulation optimization. 10 - Operation Research for Data Mining: An Application to Medical Diagnosis Shahab Derhami, Auburn University, 3301 Shelby Center, Auburn, GA, 36849, United States of America, sderhami@auburn.edu Fuzzy rule based classification systems (FRBCSs) have been successfully employed as a data mining technique where the goal is to discover the hidden knowledge in a data set and develop an accurate classification model. Despite various heuristic approaches that have been proposed to learn fuzzy rules for these systems, no exact optimization approach has been developed for this problem. We propose integer programming models to learn fuzzy rules for a FRBCS used for medical diagnosis purpose. 11 - Forecasting Surges in the Hospital Emergency Department (ED) Alexander Gutfraind, Chief Healthcare Data Scientist, Uptake Technologies, 600 W. Chicago Avenue, Chicago, IL, 60654, United States of America, sasha.gutfraind@uptake.com, Nelson Bowers, Jim Herzog, Madeline Jannotta, Ilan Kreimont, Adam Mcelhinney A major hospital system in the Chicago metro area experiences large unexpected surges in its Emergency Department (ED). Using five years of ED admissions we predict ED surges and improve scheduling of staff. Data indicates the time of arrival, rooming and discharge and acuity. Total arrivals per day cannot be predicted accurately with epidemiological climatological, calendar variables but the state of the ED could be predicted 1-4 hours in advance with high accuracy using VAR methods. 12 - A New Measure for Testing Independence Qingcong Yuan, Graduate Student, University of Kentucky, 300 Alumni Drive Apt. 166, Lexington, KY, 40503, United States of America, qingcong.yuan@uky.edu, Xiangrong Yin We introduce a new measure for testing independence between two random vectors. Our measure differs from that of distance covariance, by using expected conditional difference of characteristic functions. We propose one empirical version by slicing on one of the random vectors. This empirical measure is based on certain Euclidean distance. Its properties, asymptotics and applications in testing independence are discussed. Implementation and Monte Carlo results are also presented. 13 - Graph Based Non-isometric Curve to Surface Matching for Local Calibration Babak Farmanesh, PhD Student, Oklahoma State University, 322 Engineering North, Stillwater, OK, 74078-5016, United of traffic flows in round trips per time unit captured by the station. 8 - Intelligent Tutoring Systems: Future Paradigm of Educational Environments

Calibration can be interpreted as a curve to surface matching problem. We propose a graph-theoretic non-isometric matching approach to solve this problem using the graph shortest path algorithm in one-dimensional spaces. For higher dimensional spaces, we introduce the generalized shortest path concept to solve the matching problem. 14 - Location and Coverage Models for Preventing Attacks to Interurban Transportation Networks Ramón Auad, Associate Professor, Universidad Católica del Norte, Of. 318, Bldg. Y1, 0610 Angamos Avenue, Antofagasta, 1240000, Chile, rauad@ucn.cl, Rajan Batta We develop a binary integer programming model to solve this problem, whose objective is to maximize the expected vehicle coverage across the network over a time horizon, using decomposition heuristics. To introduce a measure of equity, we propose two sets of time constraints, considering total vehicle coverage, inequity and network coverage. We explore scalability of the model for excessively large instances. All of this features are applied to a case study in Northern Israel. 15 - An Information-based Framework for Incorporating Travel Time Uncertainty in Transportation Modeling Jiangbo Yu, University of California, Irvine, 4101 Palo Verde Rd, Irvine, CA, 92617, United States of America, jiangby@uci.edu, Jay Jayakrishnan This paper proposes a modeling framework aimed at systematically incorporating perceived uncertainty into decision making. The model uses theoretically sound concepts from information theory, communication, and cognitive science. Potential applications and implications are identified and demonstrated with examples. 16 - Database of Identified Poly and Mono ADP-ribosylated Proteins Charul Agrawal, Undergraduate Student, Indian Institute of Technology (IIT) Delhi, Room No ED-16, Himadri Hostel, Hauz Khas, New Delhi, 110016, India, agrawalcharul09@gmail.com Poly(ADP-ribose) polymerase (PARP) is a family of enzymes with 17 known members regulating post translational modification of proteins by attaching a single ADP ribose unit (MARylation) or a chain of ADP ribose (PARylation).In this study we have attempted to identify all proteins known to be modified by PARPs and the methods as well as drugs used in such studies. Our study aims to create the first ever tool for characterizing these modifications. 17 - Configuring Ecommerce Driven Supply Chains in the FMCG Sector Stanley Lim, PhD Candidate, Cambridge University, Department of Engineering, 17 Charles Babbage Road, Cambridge, United Kingdom, wtsfl2@cam.ac.uk Omnichannel has become the engine of growth in retailing. However, it remains unclear as to how distribution networks should be configured. This research will shed light through a framework development, and by drawing theories from supply chain configuration, resource based view, and transaction cost economics. Case study approach is adopted to identify the critical factors driving operational choices and seeks to elaborate the relationships between configuration, capability and performance. 18 - Benchmarking Construction and Improvement Heuristics for Classification using Markov Blankets Daniel Gartner, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, United States of America, dgartner@andrew.cmu.edu, Rema Padman This study examines construction heuristics in connection with a tabu search- based improvement heuristic for classification in high dimensional data sets. Using the UCI machine learning data repository containing benchmark instances in e.g. health care, we evaluate computation times and information about the evolution of the Markov blanket graphical models in each phase of the heuristics. We compare the performance of the approaches using evaluation measures such as classification accuracy. 19 - A Sim-heuristic Algorithm for Robust Vehicle Routing Problems with Stochastic Demand Abdulwahab Almutairi, Technology, 9 Horizon Building, Portsmouth, PO4 8EW, United Kingdom, abdulwahab.m.almutairi@gmail.com We consider the VRPSD in which customers’ demands are stochastic. We propose to model and solve the VRPSD by developing a robust optimisation model with a sim-heuristic solution method to minimise the cost while satisfying all demands. The method combines MCS with CWS in order to efficiently solve the VRPSD combinatorial optimisation problem. The results is generating very good quality solutions compared to those in the literature.

States of America, babak.farmanesh@okstate.edu, Balabhaskar Balasundaram, Arash Pourhabib

Calibration refers to the process of adjusting parameters of a computer simulation so that the simulation responses match the corresponding physical responses.

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