Informs Annual Meeting 2017

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INFORMS Houston – 2017

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There is a vast empirical literature suggesting that providing food aid in cash or vouchers is significantly more effective compared to in-kind. Yet, ours is the first study that mathematically models the aid modality selection and provides a methodology that can respond the dynamics of the environments requiring food assistance. 3 - On the Cost and Effectiveness of Packaging as a New Lever in Food Aid Supply Chain Design Mark Brennan, Massachusetts Institute of Technology, 77 Massachusetts Avenue, E38-649, Cambridge, MA, 02139, United States, mbrenn1129@gmail.com, Jarrod D. Goentzel, Prithvi Sundar, Dan Frey Recent legislation has changed from where and when US food aid can be sourced, and how it can be shipped, affecting the timeless and cost-effectiveness of relief efforts. Using data collected from a $1.7 million US food aid procurement in which new packaging types were piloted, this study shares results of the cost and effectiveness of changing in which packaging food aid is shipped. This study demonstrates how packaging can be a lever of supply chain design, and presents the advantages and limitations of including another “lever” in the US food aid supply chain. 360C Military Applications Contributed Session Chair: Laura Freeman, IDA, Alexandria, VA, United States, lfreeman@ida.org 1 - Model Predictive Control for the Flow Field in an Intermittent Transonic Wind Tunnel Jian Zhang, City University of Hong Kong, Hong Kong, jzhang398-c@my.cityu.edu.hk This study aims to design a controller to quickly reject various disturbances for the varying Angle of Attack (AoA) tests in an Intermittent Transonic Wind Tunnel (ITWT). A novel AoA model (i.e., Hammerstein model) with corresponding modeling approach is developed to characterize the influence of varying AoA on the static pressure. Finally, the flow field controller is formed as a simple Quadratic Programming (QP) problem, and the feedforward strategy is employed to compensate for the varying AoA disturbance. Simulation results and practical wind tunnel tests prove that the proposed controller can improve test precision and reduce test costs. 2 - Assessing Risk in a Military Logistics Network Brandon McConnell, North Carolina State University, 1631 Carywood Drive, Apt 1631, Cary, NC, 27513, United States, bmmcconn@ncsu.edu The U.S. Army’s adoption of an enterprise resource planning (ERP) system provides an opportunity to develop automated decision-support tools and other analytical models designed to use logistical data. This research presents a tool that runs in near-real time to assess risk while conducting capacity planning and performance analysis for a military logistics network. A goal-seeking adaptive simulation is combined with recent advances in transient queue analysis to both account for uncertainty and assess residual risk. 3 - Simulation of a Readiness Based Sparing Optimization Javier Salmeron, Naval Postgraduate School, 1411 Cunningham Road, Monterey, CA, 93943, United States, jsalmero@nps.edu, Wray John, Arnold H. Buss We develop a simulation to complement a new optimization tool that establishes inventory levels for aviation weapon systems (WS) in the U.S. Navy. We seek cost minimization while achieving required readiness for hundreds of WS, each comprising thousands of indentured parts. We employ the Vari-Metric model and a variant of a greedy heuristic algorithm. On average, the optimization slightly overestimates availability. Also, 57 of 64 WS simulated yield results within 8% difference, with a worst-case under 11%. We identify factors correlated to these differences. We test another legacy optimization tool currently in use by the Navy and find it has a larger difference in expected readiness. 4 - Robust Allocation of Resources in Reliability Growth Testing Mohammadhossein Heydari, University of Arkansas, 1898 Caton Dr, Fayetteville, AR, 72704, United States, mhheydar@uark.edu, Kelly Sullivan Reliability growth testing seeks to identify and remove failure modes in order to improve the reliability of a system. In this study, we consider the robust allocation of testing resources across the components of series and series-parallel systems. We assume that the failures of each component occur according to the AMSAA model (Crow, 1974) with uncertain parameters within a bounded uncertainty set. We develop and analyze exact solution approaches for this problem based on a cutting plane algorithm. A simulation approach is used to compare solutions from our model with solutions from an analogous deterministic optimization model. TA44

360A Nano Manufacturing Invited: Advanced Manufacturing Invited Session Chair: Chiwoo Park, Florida State University, Tallahassee, FL, 32310-6046, United States, cpark5@fsu.edu 1 - Quantifying Nanoparticle Mixing State to Account for Both Location and Size Effects Yanjun Qian, Texas A&M.University, 1501 Harvey Rd, Apt 806, College Station, TX, 77840, United States, qianyanjun09@gmail.com, Ling Dong, Xiaodong Li, Dan Yu, Hui Zhang, Zhong Zhang, Yu Ding Ripley’s K function is a favored tool in quantifying the homogeneity of the nanoparticles mixing state, a parameter is of close relevance to certain properties of the nanomaterial. Ripley’s K function assumes that the spatial points are dimensionless, however the nanoparticles form clusters or agglomerates of various sizes and shapes. Our analysis shows that using the original K function falls short of ranking the homogeneity of nanoparticle mixing. We therefore propose to revise the K function to account for both particle location and size effects. The analysis on electron microscopy images of material samples shows that the revised function is a better index to quantify the mixing states. 2 - Tensor Mixed Effects Model with Applications in Nanomanufacturing Inspection Xiaowei Yue, Georgia Institute of Technology, 755 Ferst Drive NW, ISYE, Atlanta, GA, 30332, United States, xwy@gatech.edu, Jin Gyu Park, Zhiyong Liang, Jianjun Shi Raman mapping technique has been used to do quality inspection of nanomanufacturing process. Massive high dimensional data with mixed effects are generated. The existing tensor decomposition methods cannot separate mixed effects, and mixed effects model can only handle matrix data instead of tensor data. We propose a tensor mixed effects (TME) model to handle high dimensional data with complex structure. The TME model can (i) separate fixed effects and random effects in a tensor domain; (ii) exploit the correlations along different dimensions; and (iii) realize efficient parameter estimation by a double Flip-Flop method. Simulation and case study demonstrate the efficiency and accuracy. 3 - Structural Sparsity Regularization for Inference of Lattice Structure Xin Li, Florida State University, 2525 Pottsdamer St, Building A, Suite A231, Tallahassee, FL, 32310, United States, xl12d@my.fsu.edu, Alex Belianinov, Ondrej Dyck, Stephen Jesse, Chiwoo Park We presents a regularized regression model with a two-level structural sparsity penalty applied to locate individual atoms in a noisy scanning transmission electron microscopy image (STEM). The applicability of the algorithm on determination of atom structures and identification of imaging distortions and atomic defects was demonstrated using real STEM images. We believe this is an important step toward automatic phase identification and assignment with the advent of genomic databases for materials. 360B Last Mile Aid Operations Sponsored: Public Sector OR Sponsored Session Chair: Feyza Guliz Sahinyazan, McGill University, Montreal, QC, H3A 1G5, Canada, feyza.sahinyazan@mail.mcgill.ca 1 - Community Healthcare Network in Underserved Areas: Design, Mathematical Models, and Analysis Marie-Ève Rancourt, HEC Montreal, Montreal, QC, H3T.2A7, Canada, marie-eve.rancourt@hec.ca, Marilène Cherkesly, Karen Smilowitz In this presentation, we design community healthcare networks in underserved areas. The problem consists of determining the number of community health workers and supervisors, as well as the routing and scheduling of the supervisors. We propose four set-partitioning mathematical models. Computational results are presented for a real-life case study. 2 - Food Assistance Modality Selection Problem: In Kind, Cash or Voucher? Feyza Guliz Sahinyazan, McGill University, Desautels Faculty of Management, Bronfman Building, 1001 Rue Sherbrooke O, Montreal, QC, H3A 1G5, Canada, feyza.sahinyazan@mail.mcgill.ca, Marie-Ève Rancourt, Vedat Verter TA43

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