2016 INFORMS Annual Meeting Program

WE50

INFORMS Nashville – 2016

WE50

WE53 Music Row 1- Omni DMA Text Mining Contributed Session

212-MCC Opt, Nonlinear Programming II Contributed Session

Chair: Carlos Deck, PhD Student, UC Berkeley, 4141 Etcheverry Hall, University of California Berkeley, Berkeley, CA, 94720, United States, cgdeck@berkeley.edu 1 - An Eigenvalue Decomposition Based Branch And Bound Algorithm For Nonconvex Qcqp With Convex Quadratic Constraints Qingwei Jin, Zhejiang University, School of Management, In this paper, we propose a branch-and-bound algorithm for finding a global optimal solution for a nonconvex quadratic program with convex quadratic constraints (NQPCQC). We reformulate NQPCQC by adding some nonconvex quadratic constraints induced by eigenvectors of negative eigenvalues associated with the nonconvex quadratic objective function to Shor’s semidefinite relaxation. Under the assumption of having a bounded feasible domain, these nonconvex quadratic constraints can be further relaxed into linear ones to form a special semidefinite programming relaxation. Then an efficient branch-and-bound algorithm branching along the eigendirections of negative eigenvalues is designed. 2 - Deployment Of Patrolling And Stationary Service Vehicles For Freeway Incident Management Mohsen Parsafard, University of South Florida, 14440 Hellenic Drive, Apt 206, Tampa, FL, 33613, United States, parsafard@mail.usf.edu, Xiaopeng Li, Zhenyu Wang, Pei-Sung Lin Freeway Service Patrols (FSP) are effective incident management systems to alleviate the incident related congestion in urban areas. A FSP system divides a network of freeways into a set of non-overlapping patrol beats and a number of tow trucks are then assigned to these beats. This study investigates a FSP system design problem. A mixed-integer nonlinear programming model is formulated for designing the optimal beat configuration and service vehicle allocation to maximally reduce delay, avoid secondary accident risks and mitigating fuel consumptions and emissions. Also, this study considers not only traditional patrolling vehicles or but also newly proposed stationary vehicles. 3 - Solutions Of Complementarity Problems Monotone With Respect To Parameters Vyacheslav V. Kalashnikov, Professor and Researcher, Tecnologico de Monterrey, ITESM, Campus Monterrey, Ave. Eugenio Garza Sada 2501 Su, Monterrey, 64849, Mexico, kalash@itesm.mx Nataliya I. Kalashnykova, Mariel A. Leal-Coronado In many applied problems (such as the elastohydrodynamic lubrication problem, some economic equilibrium problems, etc.), one of the important questions is if certain complementarity problem’s solution is monotone with respect to parameters. Our paper investigates this question and provides several types of sufficient conditions that guarantee such a monotonicity of the solutions to linear and nonlinear complementarity problems with parameters. In the majority of cases, it is required that the principal mapping of the complementarity problem be monotone with respect to the decision variables and, vice versa, antitone with respect to the parameters. 4 - Solving Lps Using Parametric Quadratic Programming Carlos Deck, PhD Student, UC Berkeley, 4141 Etcheverry Hall, University of California - Berkeley, Berkeley, CA, 94720, United States, cgdeck@berkeley.edu Our approach for solving a standard LP with m constraints and n variables is based on a parametric QP where we relax the inequality constraints of the polyhedron of optimal solutions in primal-dual space. Using this approach, we can solve the bad instances of the simplex method given by the deformed products of Amenta and Ziegler (1999) in a polynomial number of pivots. 866 Yuhangtang Road, Hangzhou, 310058, China, qingweijin@gmail.com, Cheng Lu, Zhibin Deng

Chair: Bill DeGray, IT Program Manager, Deloitte Services, LP, Hermitage, TN, 37076, United States, william.degray@gmail.com 1 - Cognitive Analytics For Financial Compliance Aditya Vempaty, IBM Research, Yorktown Heights, NY, United States, avempat@us.ibm.com, Elham Khabiri, Swapna Buccapatnam, Matthew Riemer, Ta-Hsin Li, Ashish Jagmohan Financial services firms require compliance with a complex set of regulatory requirements, laws, and regulators. In the face of increased regulatory enforcement, firms have significantly increased compliance spend. A major contributor to soaring compliance spend is the intensive expert manual component of current compliance processes. We propose approaches for automating key compliance processes using statistical machine learning and natural language processing techniques. We present preliminary results comparing performance against expert outcomes. 2 - On Determining The Viability Of Parametric Cost Forecasting Of Agile Software Development Projects To Improve Project Cost Forecasts Bill DeGray, IT Program Manager, Deloitte Services, LP, Hermitage, TN, 37076, United States, william.degray@gmail.com This presentation describes methods being used in a four phased investigation to determine whether parametric forecasting is a viable alternative to bottom-up forecasting for software development projects. Phase 1 (completed) - design. Phase 2 (completed) - determine if there is a relationship between the percentage of the historical project costs incurred (the response variable) and the percentage of the project schedule completed (the predictor variable). Phase 3 (in-progress) - identifying the model(s) that best describe(s) the relationship. Phase 4 will focus on development, testing, and piloting a parametric forecasting tool model based on the best regression model(s). WE54 Music Row 2- Omni Value Co-creation Sponsored: Service Science Sponsored Session Chair: Ralph D Badinelli, Professor, Virginia Tech, Blacksburg, VA, 24061, United States, RALPHB@vt.edu 1 - Empirical Analysis Of Hospital Behaviors Resulting From Value Based Purchasing Gregory Heim, Mays Business School, Texas A & M University, College Station, TX, 77845, United States, GHeim@mays.tamu.edu We examine impacts of the federal Value Based Purchasing financial incentive policy to determine whether this federal program has changed practices and processes of healthcare providers in a manner that enhances process quality and improves healthcare outcomes, thereby enhancing value for patients. 2 - Value Derivation In The Service Journey Ralph Badinelli, Virginia Tech, ralphb@vt.edu Value co-creation is accomplished in service systems through an adaptive journey by service participants in a hypernetwork of service contexts. The viability of the service ecosystem depends on the engagement decisions made by participants at each context of the journey. Predicting and controlling this path is made complex by the stigmergy enabled by social networking and other information sources. We use fuzzy models of engagement decisions and examine the role of swarm intelligence in determining the viability of service ecosystems. We justify a value derivation principle in the place of value propositions and we derive patterns of service journeys under different touchpoint strategies.

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