2016 INFORMS Annual Meeting Program

WE14

INFORMS Nashville – 2016

WE14 104D-MCC Facility Location II Contributed Session Chair: Jianmai Shi, Associate Professor, National University of Defense Technology, Changsha, 410073, China, jianmaishi@gmail.com 1 - The Maximal Covering Location Problem With Minimization Of Cardinality Of Upper Average Eric C Blair, PhD Student, University of Florida, Gainesville, FL, 32601, United States, ecblair@ufl.edu, Matthew Norton We present a reformulation of the Maximal Covering Location Problem (MCLP) using the new concept of Cardinality of Upper Average (CUA). In the MCLP, a fixed number of facilities are located to minimize the number of customers that must travel farther than some maximum desirable distance to the nearest facility. In the new formulation utilizing CUA, the number of customers with the largest travel distances whose average travel distance to the nearest facility is equal to the maximum desirable distance is minimized. The resulting problem is reduced to a mixed-integer linear program. We demonstrate the advantages of the new formulation with a numerical example. 2 - The Optimal Planning Of Electric Vehicle Battery Swapping Network With Fuzzy Customer Satisfaction Fang Guo, Huazhong University of Science and Technology, 1037 Luoyu Road, Hongshan District, WuHan,, WuHan, 430074, China, fang_guo@hust.edu.cn Key to the mass adoption of electric vehicles is the establishment of sufficient battery service Infrastructure network based on customer behavior and psychology. We present an EV battery swapping network planning with fuzzy customer satisfaction, which aims to determine the location and service capacity strategy of stations simultaneously with the consideration of customer satisfaction. A heuristic algorithm is proposed to solve the problem. Furthermore, we conduct the parameter analysis when EVs are used in the practice of the City Cluster in the Middle Reaches of the Yangtze River in China. 3 - Logistics Service Network Design For Humanitarian Response In East Africa Marie-Eve Rancourt, Université du Québec à Montréal, 2920 Chemin de la tour, CIRRELT, Montreal, QC, H3T 1J4, Canada, marie-eve.rancourt@cirrelt.ca, Émilie Dufour, Gilbert Laporte, Julie Paquette The United Nations Humanitarian Response Depot (UNHRD) is an important humanitarian logistics service provider that manages a network of depots. This research project aims to analyze the potential benefits of adding a regional distribution center in Kampala, Uganda, to its existing network. To this end, we used fieldwork, simulation, optimization and statistical analyses to assess the costs of prepositioning relief items in Kampala and to propose a robust stocking solution. The UNHRD has already started to implement the solution proposed in this study, which should result in a mean cost reduction of around 21%. 4 - Joint Deployment Of Electric Car Charging Stations And Servers On A Road Network Jianmai Shi, Associate Professor, National University of Defense Technology, Changsha, 410073, China, jianmaishi@gmail.com, Yue Wang, Zhong Liu, Yajie Liu A joint charging station location and charging piles (servers) configuration problem for electric cars is studied, where the service capacity of the station depends on the number of servers. The problem is an extension of the Flow- Capturing location problem, and an integer programming model is proposed to maximize the overall car flow served, subject to a finite budget. A heuristic algorithm is developed to solve the problem, and the performance of the algorithm is tested by networks with different scales. We finally present a case study based on a practical road network in China.

convenience, it has also opened up the possibilities for devastating cyber-attacks. This study demonstrates a data and text mining approach to identify SCADA systems on Internet of Things. We also use state-of-the-art vulnerability assessment techniques to identify the vulnerabilities of these devices. The results of this study indicate that many SCADA vendors are vulnerable to various exploits. 2 - Key Conversation Trends And Patterns About Electronic Cigarettes On Social Media Wenli Zhang, University of Arizona, Tucson, AZ, United States, wenlizhang@email.arizona.edu, Sudha Ram” Electronic cigarettes (e-cig) usage has increased exponentially over the last few years and are perceived to be safer alternative to cigarettes use. In order to understand the public health impact of e-cig, a better understanding of population-wise use patterns, perceptions regarding the use and abuse liability of e-cig should be developed. However traditional survey is not adequate to get such information. The research objective of this study is to explore using social media data to identify key conversations, trends, and patterns about the usage of e-cig by using natural language processing, word embedding, topic modeling, content and sentiment analysis, and social network analysis. 3 - Stock Movements Prediction Using Textual And Technical Data Juxihong Julaiti, The Pennsylvania State University, 445 Waupelani Drive, J01, State College, PA, 16802, United States, juxihongjulaiti1225@gmail.com Predicting stock movements is one of the most appeal topics for researchers since an accurate predictive enables gain wealth, as well as the rapid progress of data acquisition has made the vast amount of data available. In this paper, we apply different machine learning techniques to predict the daily stock movement. In particular, we use the type, title of news articles of the current day that are related to the interested company from the Wall Street Journal, as well as its stock volume of the day. The result of predicting Google’s stock changes indicates big drops or big growths are easier to capture, and the average AUC and accuracy of the Gaussian Naïve Bays are 0.83 and 0.97. Nonlinear Optimization Algorithms III Sponsored: Optimization, Nonlinear Programming Sponsored Session Chair: Feng Qiang, Argonne National Laboratory, 9700 S Cass Avenue, Argonne, IL, 60439, United States, fqiang@anl.gov 1 - Analysis Of The Proximal Quasi Newton Algorithm In Solving Convex Composite Problems Hiva Ghanbari, Lehigh University, Bethlehem, PA, 18015, United States, hig213@lehigh.edu, Katya Scheinberg In this work, we analyze the convergence properties of an inexact proximal quasi-Newton algorithm to solve composite optimization problems in the case of strong convexity. We consider solving subproblems to the eps-optimality while an inexact sufficient decrease condition is checked to be satisfied at each iteration. Furthermore, we apply the Nesterov’s accelerated scheme to present the accelerated proximal quasi-Newton algorithm. In addition to the theoretical properties of the resulting algorithm, the numerical results will be presented. 2 - Parallel Problem Generation For Nonlinear Programming Problems In Julia Feng Qiang, Argonne National Laboratory, Lemont, IL, 60439, United States, fqiang@anl.gov, Joseph A Huchette, Miles Lubin, Cosmin Petra Large scale optimization problems usually have rich structural properties. In this talk, we present StructJuMP, a parallel modeling environment for structured optimization problems. Built as a parallel extension to modelling language JuMP, StructJuMP offers additional syntax to specify blocks of the problems and an MPI- based parallelization of the model generation. We demonstrate StructJuMP capabilities for the specification of power grid optimization problems on an HPC cluster at Argonne National Lab. 3 - Regularized Primal And Dual Methods For Convex Quadratic Programming Elizabeth Wong, University of California-San Diego, elwong@ucsd.edu We discuss active-set methods for convex quadratic program with general equality constraints and simple lower bounds on the variables. In the first part of the talk, two methods are proposed, one primal and one dual. In the second part of the talk, a primal-dual method is proposed that solves a sequence of quadratic programs created from the original by simultaneously shifting the simple bound constraints and adding a penalty term to the objective function. Numerical results are presented for the combined primal-dual active-set method. WE17 105B-MCC

WE15 104E-MCC Text Mining II Sponsored: Artificial Intelligence Sponsored Session

Chair: Weifeng Li, University of Arizona, weifengli@email.arizona.edu 1 - Exploring Scada Devices And Their Vulnerabilities On The Internet Of Things Sagar Samtani, The University of Arizona, sagars@email.arizona.edu Much of modern society is reliant on critical infrastructure. Much of this infrastructure is controlled and managed by Supervisory Control and Data Acquisition (SCADA) systems. Recent years has seen an increase in internet connectivity of SCADA systems. While this has resulted in an increased level of

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