2016 INFORMS Annual Meeting Program

POSTER SESSION

INFORMS Nashville – 2016

Taxi Sharing Mustafa Lokhandwala, Purdue University, 241 Sheetz Street, Apt 14, West Lafayette, IN, 47906, United States, mlokhand@purdue.edu New York City has one of the busiest transportation systems in the world. This study focuses on a part of this network i.e. taxis and attempts to analyze the benefit of Taxi Sharing using simulation software and optimization techniques. The focus of our study will be to build an agent-based simulation model using trip data obtained from the New York Taxi and Limousine Commission, model the decision making methodologies of the agents in a taxi sharing scenario and run this model using the most recent trip data within New York City. The result from this experiment will be to optimize the number of taxis operating on the streets of New York City and also quantify the economic and environmental benefits of the same. Acceleration Of A Communication Efficient Distributed Dual Block Descent Algorithm Chenxin Ma, Lehigh University, 200 West Packer Avenue, Bethelehem, PA, 08801, United States, chm514@lehigh.edu Distributed optimization algorithms for very large-scale machine learning suffer from communication bottlenecks. Confronting this issue, a communication- efficient primal-dual coordinate ascent framework (CoCoA) and its improved variant CoCoA+ have been proposed, achieving a convergence rate of O(1/t) for solving empirical risk minimization problems with Lipschitz losses. In this paper, we propose an accelerated variant of CoCoA+ and show that it has a rate of O(1/t2) in terms of reducing dual suboptimality. Our analysis is also notable in that our convergence rate bounds involve constants that, except in extreme cases, are significantly reduced. Enhancing Operational Performance Of Emergency Room Team Maryam M Mahdikhani, PhD Candidate, Rutgers University, 1 Washington Park, Room 1019C, Newark, NJ, 07102, United States, m.mahdikhani@rutgers.edu The study investigates the effect of situational awareness concepts on the operational performance of involved agents at emergency rooms to increase the efficiency of performance. Applying ABM techniques makes contributions to illustrate that the effect of which attributes for which agent is more significant than others. We considered three main agents by developing their attributions and variables through random function. Furthermore, situational awareness is described by availability of authority in case of problems, supervisor feedback, and resource availability. An Integrated Black Topsis And Grey Linear Programming Approach To Deal With Uncertainty And Confidence Level Of Decision Makers Hanif Malekpoor, PhD Student, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, United Kingdom, H.Malekpoor@uea.ac.uk In order to deal with uncertainty of Decision Makers (DMs) opinions in supplier selection, applying interval valued data is a popular method. However the level of confidence, DMs have about their judgments, is also significant. In addition the supplier’s information related to constraints of order allocation problem is not always trustable and precise. In this research to overcome the two aforementioned problems we have developed an integrated approach for order allocation, using Black-TOPSIS (TOPSIS with interval numbers which their upper and lower bounds are also grey numbers) and multi objective grey linear programing to determine the best supplier and order quantity from each suppliers. Development Of A Least-cost Diet For The Crew Of A Brazilian Navy’s Warship Ernesto Rademaker Martins, Commander, Brazilian Navy, Arsenal da Marinha no Rio de Janeiro (AMRJ), Rua da Ponte S/N, Ilha da Cobras, Centro, Rio de Janeiro, 20091000, Brazil, radmart@yahoo.com.br, Marcos Santos, Jessica Alves Souza, Fabrício Costa Dias, Marcone Freitas Reis Develop an analytical model for the meals served to the crew of Brazilian Navy’s warship. Such a diet should take into account the nutritional needs of adult men aged 18-45 years, as well as the specifics of the work activities performed aboard a warship. Due to its deterministic nature, sought a solution to the problem in the light of linear programming, specifically the Simplex Method. The analytical model was established by the data obtained in the Brazilian Navy’s normative legislation. The solution of the mathematical model in screen can support the decision of the management of the military organization, to contribute to the fulfillment of the Brazilian’s Law. Modeling Strategic Decisions In Football Christopher G McCord, Massachusetts Institute of Technology, Cambridge, MA, United States, mccord@mit.edu Football has long been recognized as one of the most strategically advanced professional sports in the US. A team must continually take into account many different factors when making decisions. In this work, I present a probabilistic model for the decisions an NFL team may face during the course of the game. I then present the strategy that maximizes the team’s probability of winning in various situations, as well as a measure of uncertainty for each decision. Finally, I

compare the model’s optimal decisions with the observed strategies of NFL teams and hypothesize why coaches behave sub-optimally in many situations. A Novel Distributed Coordinated Approach For Real-time Signal Control Mehrzad Mehrabipour, Graduate Research Assistant, Washington State University, 1630 NE valley Rd, Pullman, WA, 99164, United States, mehrzad.mehrabipour@wsu.edu, Ali Hajbabaie This study develops a distributed-coordinated methodology for traffic signal timing optimization problem. Our formulation and solution methodology distribute the network level signal timing optimization problem to intersection level. We formulated a mathematical programing model for each intersection, based on the cell transmission model and created coordination between them to avoid finding locally optimal solutions. The neighboring intersections coordinate their decisions to avoid long queues. We also proposed a rolling horizon solution algorithm and applied it to several case study networks under various demand patterns and observed very promising results. Optimal Parking Utilization Management Under Uncertain Demand Amir Mirheli, Washington State University, 405 Spokane Street, Sloan 242, Pullman, WA, 99163, United States, amir.mirheli@wsu.edu, Leila Hajibabai Excessive cruising to find parking spots contributes to additional delays and imposes indirect costs, safety, and health concerns, particularly in congested urban areas with limited parking capacity. This research develops a bi-level stochastic dynamic parking management model under uncertain demand to simultaneously minimize total costs due to drivers’ decisions, maximize parking agency’s revenue, and push parking utilization towards a target occupancy. The problem is solved using a hybrid technique including an approximate dynamic programming with an embedded single-level conversion. Numerical experiments show the performance of the proposed algorithm and draw managerial insights. Regularized Discriminant Analysis For Multisensory Damage Detection And Decision Fusion Using Lamb-waves Spandan Mishra, Florida State University, 2005 Levy Avenue, Tallahassee, FL, 32310, United States, sm11ax@my.fsu.edu, Arda Vanli, Fred Huffer We have propose a for damage detection which does not require an intermediate feature extraction step and therefore more efficient in handling data with high- dimensionality. A robust discriminant model is obtained by shrinking of the covariance matrix to a diagonal matrix and thresholding redundant predictors without hurting the predictive power of the model. The shrinking and threshold parameters of the discriminant function are estimated to minimize the classification error. Furthermore, bayesian decision-fusion formulation is used to improve the damage classification obtained from the regularized linear discriminant analysis approach Identification Of Optimal Partition For Semidefinite Optimization Ali Mohammad Nezhad, PhD Candidate, Lehigh University, 200 West Packer Ave, Mohler lab, Bethlehem, PA, 18015, United States, alm413@lehigh.edu The concept of optimal partition was originally introduced for linear optimization and linear complementary problems and subsequently extended to semidefinite optimization. For linear optimization and sufficient linear complementary problems, the optimal partition and a maximally complementary optimal solution can be identified in strongly polynomial time. In this paper, under no assumption on strict complementarity, we formalize the optimal partition concept for semidefinite optimization and present a methodology for an $\epsilon$-feasible maximally complementary solution. Should We Decrease Corn Subsidies And Subsidize Fruits & Vegetables? Philip F. Musa, Associate Professor and Programs Director, University of Alabama-Birmingham, PO Box 55544, Birmingham, AL, 35255, United States, musa@uab.edu This Poster calls for programmed reductions of Corn Subsidies with a corresponding ramping up of Subsidies for fruits and vegetables. If implemented, this Public Health initiative could have a dramatic positive impact on Obesity reduction, its associated comorbidities, and healthcare costs in the USA. It should also enhance Quality of Lives. Endogenous Time Preference And Exhaustible Resource Use Makiko Nagaya, Showa Women’ University, Tokyo, Japan, makiko.nagaya@gmail.com This paper re-examine a classical topic of exhaustible resource use on the basis of recent developments in time preference models. We analyze the effects of endogenous time preference on dynamic properties of resource use, contrasting to classical Hotelling’s results. Finally, we introduced a concept of minimum required level of consumption.

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