2015 Informs Annual Meeting

POSTER SESSION

INFORMS Philadelphia – 2015

48 - Big Data Analytics for Singapore Public Train System Nang Laik Ma, Senior Lecturer, SIM University, 461 Clementi Road, Singapore, 599491, Singapore, nlma@unisim.edu.sg, Beng Yee Wong This paper focus on capacity planning of the Singapore public transport system. We analyse the commuters’ travelling patterns from historical transactions data. Secondly, by simulating train schedule and capacity constraints, the model mimicked the real-world situations to generate the waiting time for each commuter. Finally, a web-based visualization tool is created to provide the average waiting time for the next train at the station to enhance the commuter’s experience. 49 - Hospital Residents Problem: A Survey Including a New Variant Kaitlyn Manley, College of Charleston, 66 George St, Charleston, SC, 29424, United States of America, manleykm@g.cofc.edu, Tyler Perini, Amy Langville We survey several variations of the Stable Matching Problem, including the Hospital Residents Problem used to assign American medical residents to hospitals. We also present a new variation of the stable matching problem that uses an binary integer linear program to determine the minimum number of interviews that hospitals should conduct in order to still maximize the number of residents assigned. 50 - Exploring the Multi-objective Portfolio Tradespace Simon Miller, Graduate Student, Penn State Applied Research Lab, P.O. Box 30, State College, PA, 16804, United States of America, ses224@arl.psu.edu, Gary Stump, Sara Lego, Michael Yukish Faced with strategic choices, senior decision makers must often make trades to meet competing requirements. In collaboration with the U.S. Army, ARL has developed tools and methods to treat large scale, multi-objective optimization problems for binary portfolios with dynamic constraints. Methodology and implementation schema for real-world cases are presented, highlighting the ability to balance a combinatorial explosion of parameters in complex trades spaces with the need for timely decisions. 51 - Experimental Designs for Metal Detectors at Large Venues Christie Nelson, Rutgers University, CCICADA, 4th Floor, CoRE building, 96 Frelinghuysen Rd, Piscataway, NJ, 08854, United States of America, christie.l.nelson.phd@gmail.com, Paul Kantor, John Edman, Vijay Chaudhary Walk-through metal detectors (WTMDs) are being used increasingly more as a security measure at large events, particularly at stadiums. Currently, WTMDs are tested using a robotic tester which tests metallic objects at level heights by sending them straight through at a constant speed. However, this is not a proper representation of how a person would enter the WTMD. We will show that the way a person walks through the WTMD impacts detection rate through our experimental results. 52 - Leading Metrics for Progress Measurement and Performance Assessment in Construction Projects Resulali Orgut, Graduate Research Assistant, North Carolina State University, Dept. of Civil, Cons. and Env. Eng., 2510 Stinson Dr., 222 Mann Hall, Raleigh, NC, 27695, United States of America, reorgut@ncsu.edu, Jin Zhu, Mostafa Batouli, Ali Mostafavi, Edward Jaselskis Progress measurement and performance assessment are critical to the management of construction projects. We perform statistical analyses to highlight key indicators for successful construction project controls by using data collected through an online survey from 27 companies. We analyze core metrics commonly used in the construction industry to develop guidelines for improving their reliability and recommend practices for interpreting metrics and indicators. 53 - Toward Consistent and Efficient Anomaly Detection in Hyperspectral Imagery Todd Paciencia, USAF, AF/A9, Pentagon, Washington D.C., United States of America, todd.j.paciencia.mil@mail.mil This research will showcase development of an approach to making an unsupervised anomaly detector for Hyperspectral Imagery (HSI). The algorithm is developed to be robust to different image scenes, different sensors, and noisy spectral bands. Specifically, fusion of spectral, spatial, and Signal-to-Noise information is used, in combination with a factor analysis approach, to identify anomalies. The algorithm is shown to be desirable when compared to current state-of-the-art techniques. 54 - Comprehensive Performance Evaluation of High-gravity Carbonation Process in the Steelmaking Industry Shu-Yuan Pan, National Taiwan University, No 71 Chou-Shan Rd., Taipei, 10673, Taiwan - ROC, d00541004@ntu.edu.tw, Pen-chi Chiang An integrated portfolio of multi-waste treatment (steelmaking slag and wastewater) combined with CO2 capture in the steelmaking industry can be achieved by the high-gravity carbonation (i.e., HiGCarb) process using a rotating packed bed (RPB). In this study, the HiGCarb process was comprehensively

evaluated according to engineering, environmental, and economic (3E) criteria using a cradle-to-gate life-cycle approach. 55 - Analysis on the Effect of Energy Efficient Technologies in Industry Sector using Times Model Sang Yong Park, Senior Researcher, Korea Institute of Energy Research, Yuseong-gu, Gajeong-ro 152, Daejeon, 305-343, Korea, Republic of, gspeed@kier.re.kr, Jong Chul Hong, Nyunbae Park, Boyeong Yun The South Korea established energy policy which is focusing demand management rather than energy supply to secure a stable energy supply and to cope with climate change efficiently through 2nd national energy basic plan in 2014. This research developed energy system model which can analyze the effect of energy efficient technologies on demand management based on TIMES(The Integrated MARKAL-EFOM System) model and conducted case study on industry sector in Korea. 56 - The Humility Project: NMF and Other Matrix Factorizations for Textual Analysis Tyler Perini, Student, College of Charleston, 66 George St, Charleston, SC, 29424, United States of America, perinita@g.cofc.edu, Amy Langville This is one of the first studies on the use of matrix decompositions as the primary engine for describing and predicting psychological characteristics in a corpus of language data. With text parsing tools, large written samples are parsed into a sparse matrix. A low-rank matrix factorization of a weighted version of this matrix is then used to determine which documents are humble and which are not humble. Three factorizations, the SVD, NMF, and weighted NMF, are compared. 57 - Distributed Online Modified Greedy Algorithm for Networked Storage Operation under Uncertainty The optimal control of energy storage networks in stochastic environments is an important open problem. This paper provides an efficient algorithm to solve this problem with performance guarantees. A sub-optimality bound for the algorithm is derived which can be minimized by solving a semidefinite program. Distributed implementation is derived based on alternating method of multipliers. Numerical examples verify our theoretical performance bounds and demonstrate the scalability of the algorithm. 58 - Should Retailers Adopt 3d Printing? Sharareh Rajaei Dehkordi, PhD Candidate, New Jersey Institute of Technology, University Heights, Newark, NJ, 07102, United States of America, sr552@njit.edu, Wenbo Cai Should retailers provide 3D printing services in addition to the traditional off-the- shelf product? We answer the question by examining retailers’ optimal joint decisions on his inventory management policy and pricing scheme while considering consumers’ heterogeneous preferences for self-designed, 3D printed products vs. off-the-shelf products. We use a multi-server queue with limited capacity to capture customers’ production selection process and its impact on the retailer’s expected profit. 59 - Stochastic Network Design with Decision-dependent Uncertainties Nathaniel Richmond, University of Iowa, 14 MacLean Hall, Iowa City, IA, 52242, United States of America, nathaniel-richmond@uiowa.edu Little research has been conducted on stochastic network design problems in which the probability distribution of future random events is affected by prior actions. However, such problems are ubiquitous and important. For example, planned reinforcements of a power network directly influence which nodes are more likely to fail. We present a stochastic two-stage programming model with decision-dependent uncertainties, discussing solution methods for the associated unique computational challenges. 60 - Scheduling Part-time Employees with Interactive Optimization Robert Rose, President, Optimal Decisions LLC, 4 Kirby Lane, Franklin Park, NJ, 08823, United States of America, robertl.rose@verizon.net Many employee scheduling problems are very challenging: they are hard combinatorial optimization problems that contain multiple objectives and ‘soft’ constraints. Such problems do not lend themselves to a pure optimization approach. A ‘Human Centered’ approach, will be described: an initial schedule is generated analytically through a series of heuristic procedures, and a final schedule is produced using an interactive graphics module. A prototype scheduling program will be demonstrated. Junjie Qin, PhD Candidate, Stanford University, 126 Blackwelder Ct, 1004, Stanford, CA, 94305, United States of America, jqin@stanford.edu

315