Informs Annual Meeting 2017

TC40

INFORMS Houston – 2017

TC41

2 - Predicting Choice Quality with Decision Style, Cognitive Reflection and Decision Environment Tommi Juhani Pajala, Aalto University, Melkonkatu 19 A.29, Helsinki, 00210, Finland, tommi.pajala@aalto.fi Psychological measures of decision style are rarely used in economic decision research. However, they could have value in explaining individual differences in a Multiple Criteria Decision Making task. I investigate whether decision style and cognitive measures together with the decision environment can explain choice quality. 159 participants answered the psychological measures and made 26 choices in a setting with six alternatives and six criteria. Low Cognitive Reflection and high Alternative Search were related to higher choice quality. Other decision style variables showed no effects. Conclusions are robust to a variety of model specifications, software packages, and priors. 3 - Approximated Set-valued Mapping Approach for Handling Multi-objective Bilevel Problems Pekka Malo, Aalto University School of Business, Runeberginkatu 22-24, Helsinki, 00100, Finland, pekka.malo@aalto.fi, Ankur Sinha, Kalyanmoy Deb A significant amount of research has been done on bilevel optimization problems both in the realm of classical and evolutionary optimization. However, the multiobjective extensions of bilevel programming have received relatively little attention from researchers in both the domains. In this paper, we develop insights into multiobjective bilevel optimization through theoretical progress made in the direction of parametric multiobjective programming. We introduce an approximated set-valued mapping procedure that would be helpful in the development of efficient evolutionary approaches for solving these problems. 4 - Multi-criterion Optimization using Evolutionary Algorithms Kalyanmoy Deb, Michigan State University, Electrical & Computer Engineering, 428 S. Shaw Lane, East Lansing, MI, 48824, United States, kdeb@egr.msu.edu In this talk, we shall present a 25 years of research and application of multi- criterion optimization and decision-making using evolutionary algorithms. The so-called EMO field, started in early nineties, have become a mainstream research area within evolutionary computation, with 500+ PhD theses, commercial softwares, and high impacting (one having 24000 citations) journal papers. 352E 2017 INFORMS Prize Winner Sponsored: INFORMS Prize Sponsored Session Chair: Tarun Mohan Lal, Mayo Clinic, Rochester, MN, 55905, United States, mohanlal.tarun@mayo.edu 1 - Informs Prize Winner Showcase – the Walt Disney Company Dayana Cope, The Walt Disney Company, P.O. Box 10000, Lake Buena Vista, FL, 32830, United States, dayana.cope@disney.com, Peter Buczkowski, Haining Yu This presentation will include a summary of the Prize winning application submitted by The Walt Disney Company. 2 - Analysis in the United State Air Force: 2017 Informs Prize Presentation Mark Gallagher, Doctorate, United States Air Force, Arlington, VA, United States, mark.a.gallagher16.civ@mail.mil The Secretary of the Air Force signed our winning nomination for the INFORMS Prize. We highlighted 3 exemplar topics of aircraft repair, nuclear deterrence, and testing. We had 17 additional topics in operation effectiveness, logistics, manpower, acquisitions, and cost analysis. Leaders from Congress, US and allied defense forces, industry, professional societies, and academia endorsed the Air Force. We summarized recent Air Force research, publications, and awards. We discussed the history of operations research in the Air Force along with contributions to the foundations of operations research. We conclude with how the Air Force develops, trains, and organizes analysts. TC40

352F Health Care, Public Health Contributed Session Chair: Xin Ding, University of Houston, Houston, TX, United States, xding@uh.edu 1 - Holistic Data Analytics and Lean in Architectural Healthcare Pre-design As healthcare systems implement EMR to store key information, exploring this data becomes crucial to strongly support process improvement initiatives seamlessly aligned with the schematic design process prior to any construction. Building new ORs adjacent to existing ORs adds more complexities during design phases since considering multiple transitional phases without deteriorating quality of service. Therefore, applying holistic data analytics, along with process analysis techniques, enables all members to understand pros and cons with respect to KPIs. Consequently, the schematic design process is better coordinated with all known and potential needs from clients. 2 - On Reducing Waiting Time for Specialists in Emergency Department Cheng Zhu, McGill University, 701-801 Sherbrooke Est, Montreal, QC, H2L.0B7, Canada, cheng.zhu@mail.mcgill.ca, Beste Kucukyazici From Emergency Department (ED) decision makers’ perspective, we first decide the optimal specialist response policies for time-dependent patient arrivals, and then propose the optimal patient prioritization policies accordingly, in order to reduce the total LOS. Parameters are derived from 40,000 annual ED visits in a local hospital, and verified with ARENA simulation. 3 - Process Innovation in the Pharmaceutical Industry Ivan Lugovoi, HEC Paris, 1 Square Theodore Judlin, Paris, 75015, France, ivan.lugovoi@hec.edu Using a unique dataset of process - patent expert evaluations, we explore the benefits from process innovation. Combining our data with the sales of eighty generic pharmaceutical products over a ten-year period we find that process- patent activation is associated with a significant increase in a company’s market share. To explain what drives this effect we evaluate process innovation across three dimensions: novelty, strength and depth. We find that two of these dimensions are mainly responsible for explaining the effect: i) the strength of a firm’s process-patent portfolio for a given product and ii) the depth of a firm’s process-patent portfolio for a given product. 4 - Does Hospital Operational Data Contain Signals of Resiliency and Safety Risk? Sung Nam Hwang, Data Analytics and Senior Modeling Specialist, CallisonRTKL, 1717 Pacific Ave, Dallas, TX, 75201, United States, shwang@rtkl.com, Cortney Asberry Acute care nurses enhance resiliency and enable patient care units to function under varying conditions by adjusting their work to meet ever changing patient needs. Adaptive strategies such as early task initiation, task deferral and delegation vary by workload state. We identify strategies frequently employed by nurses in normal, high and extreme workload states. We then explore whether “echoes” of these adaptive behaviors can be identified in ambient data generated by medication dispensing, nurse call and other systems used in care delivery. Analysis of ambient data may inform patient safety and improve the work experience of nurses by providing early signals of workload state transitions. 5 - The Impact of Focus Strategy and Market Competition on Cost Efficiency Xin Ding, University of Houston, T2-230C, Technology I I.Building, Houston, TX, 77204, United States, xding@uh.edu, Xiaosong David Peng, Gregory R. Heim In this study, we examine the longitudinal impact of focus strategy on cost efficiency in U.S. hospitals. We hypothesize that as the level of focus increases, hospital cost efficiency increases at a decreasing rate. In addition, we also hypothesize that focus helps improve cost efficiency in a competitive market when specialty hospitals are not present. Lastly, we propose that focus strategy has the strongest effect on cost efficiency for proprietary hospitals in highly competitive markets. Dana Womack, PhD Candidate, Oregon Health & Science University, 48230 NW. Narup Road, Portland, OR, 97106, United States, womacda@ohsu.edu, Michelle Rose Hribar, Nancy Vuckovic, Paul Gorman

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