2016 INFORMS Annual Meeting Program

MD67

INFORMS Nashville – 2016

MD67 Mockingbird 3- Omni IEEE T-ASE Invited Session II General Session Chair: Jingshan Li, University of Wisconsin - Madison, jli252@wisc.edu 1 - Sparse Modeling And Recursive Prediction Of Space-time Dynamics In Stochastic Sensor Networks Hui Yang, Penn State University, huy25@engr.psu.edu Wireless sensor network has emerged as a key technology for monitoring space- time dynamics of complex systems, e.g., and body area sensor network. However, sensor failures are not uncommon in traditional sensing systems. As such, we propose the design of stochastic sensor networks to allow a subset of sensors at varying locations within the network to transmit dynamic information intermittently. Experimental results on real-world data and different scenarios of stochastic sensor networks demonstrated the effectiveness of sparse particle filtering to support the stochastic design and harness the uncertain information for modeling space-time dynamics of complex systems. 2 - Integration Of Data Fusion Methodology And Degradation Modeling Process To Improve Prognostics Kaibo Liu, UW-Madison, 1513 University Avenue, Madison, WI, 53706, United States, kliu8@wisc.edu, Shuai Huang The rapid development of sensing and computing technologies has enabled multiple sensors embedded in a system to simultaneously monitor the degradation status of an operation unit. Unlike other existing data fusion methodologies that treat the fusion procedure and the degradation modeling as two separate tasks, this paper aims at solving these two challenging problems in a unified manner. A case study that involves a degradation dataset of an aircraft gas turbine engine is implemented to numerically evaluate and compare the prognostic performance of the developed health index with existing literature. 3 - Bottleneck Analysis To Reduce Surgical Flow Disruptions: Theory And Application Xiang Zhong, UW-Madison, xzhong4@wisc.edu, Jingshan Li The work flow of surgical operations in emergency department and operating rooms can be interrupted due to various disruptions. Reducing such disruptions is of significant importance to ensure successful operations. In this paper, we introduce a continuous-time Markov chain model to analyze the disruptions and their impacts. A continuous improvement method is developed to identify the bottleneck disruption, so that reducing the interruption time and frequency of the bottleneck can lead to the largest improvement. An application of the method at an emergency department of a large academic medical center is presented to illustrate the effectiveness of the model and the improvement approach. 4 - Integrating Optimal Simulation Budget Allocation And Genetic Algorithm To Find The Approximate Pareto Patient Flow Distribution Zekun Liu, Washington University, liu.zekun@wustl.edu The imbalanced development among different levels of hospitals caused by the irrational patient flow distribution has become a major social issue in China’s urban healthcare system. In this work, we propose a methodology framework integrating discrete-event simulation, multi-objective optimization and multi- objective optimal computing budget allocation to find the optimal macro-level patient flow distribution. A case study validating the optimization framework shows the Pareto optimal patient flow distribution can improve overall system performances.

2 - Measurement Error Of Binary Quality Inspections In Industry Thomas Akkerhuis, University of Amsterdam, T.S.Akkerhuis@uva.nl The evaluation of the reliability of binary measurements, such as quality inspections in industry, is challenging. This especially holds in gold standard unavailable situations, where the true conditions of the inspected items are unobservable. Our studies show that methods in literature for such evaluation perform poorly. We found that binary measurement error can be decomposed in a random and a systematic part. Although this is a well-known decomposition for numerical measurement, it is a new insight for binary measurement. It turns out that, in a gold standard unavailable situation, generally only the random component is identifiable. We have developed a robust and efficient method to do so. 3 - Qfd Customer-requirement Prioritization Based On The Law Of Comparative Judgments Domenico Augusto Maisano, Associate Professor, Politecnico di Quality Function Deployment (QFD) is a structured process to design and develop products/services that better fulfill customers’ requirements (CRs). The initial collection and analysis of the CRs is particularly critical, as any distortion can propagate to the whole process results. The focus of this article is on the prioritization of CRs, which can be improved by introducing a new prioritization technique based on the Thurstone’s Law of Comparative Judgment. The greatest strength of this technique is combining a refined theoretical model with a simple and user-friendly data collection process. The description is supported by a realistic application example. MD69 Old Hickory- Omni Routing and Allocation in Military Operations Sponsored: Military Applications Sponsored Session Chair: Alexandra M Newman, Colorado School of Mines, 1104 Maple Street, Golden, CO, 80401, United States, anewman@mines.edu 1 - Minimum Risk Routing Through A Mapped Mine Field Chris Richards, Colorado School of Mines, chrichar@mymail.mines.edu A typical risk-additive routing model in a network or network representation of continuous space may be unrealistic. We present an alternative ``threat-additive model’’ formulated as an integer program. We then develop a specialized, shortest-path approximation to this model. In a realistic model of a ship seeking to traverse a mapped minefield with minimum risk, we show that the approximation provides ``true risk’’ while constraining computation time via implicit enumeration. 2 - Building An Optimization-based, Decision Support System For Routing Vehicles For Randomized Inspections Doug Altner, MITRE Corporation, daltner@mitre.org, Justin Nave, Abby Ng Suppose we want to maximize the number of 500,000+ sites that 60+ vehicles can visit subject to constraints on time, area covered, overnight travel, and the mix of sites selected, while also ensuring selections are “sufficiently random” and vehicle territories are “well defined”. This talk discusses how we heuristically solved this problem, and how we turned our methods into an optimization-based, decision support system for our customer. 3 - Daily Aircraft Routing For Amphibious Ready Groups Robert Dell, Professor of Operations Research, Naval Postgraduate An Amphibious Ready Group (ARG) consists of ships capable of conducting flight operations that routinely require the transport of personnel and cargo (PMC) to remain operationally viable. Planning PMC transport for an ARG and nearby airfields is a unique vehicle routing problem (VRP) characterized by a heterogeneous capacitated fleet, two cargo types, multiple depots, disjoint time windows, and synchronized routing of two aircraft required between some but not all node pairs. We solve most realistic instances optimally but solution time can become excessive so we also solve instances using a metaheuristic. This talk describes this unique VRP, our metaheuristic and our computational experience. Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy, domenico.maisano@polito.it, Fiorenzo Franceschini School, Monterey, CA, United States, dell@nps.edu, Travis Hartman, Connor McLemore, Ertan Yakici

MD68 Mockingbird 4- Omni

Quality Engineering Invited Session Sponsored: Quality, Statistics and Reliability Sponsored Session

Chair: Murat Caner Testik, Prof.Dr., Hacettepe University, Hacettepe Universitesi, Muhendislik Fakultesi Endustri Muhendisligi Bolumu, Ankara, 06800, Turkey, mtestik@hacettepe.edu.tr 1 - Metamodel Based Method For Optimization Of Multilayer Thin Film Architecture Srikant Nekkanty, Intel Corporation, nekkanty2001@gmail.com, Danel Draguljic, Thomas Santner, Angela Dean, Rajiv Shivpuri The application of thin, hard coatings is one of the most effective ways to protect engineering components operating under heavy contact. We describe a metamodel based approach for improving the performance of a multilayer coating architecture using finite element models. From finite element models, the stresses in the coating material were evaluated and used to build the metamodel for optimizing the multilayer system. The complexity of this engineering application involved (1) a nonrectangular input region of coating designs and (2) opposing objectives to be minimized simultaneously.

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