2015 Informs Annual Meeting

TB64

INFORMS Philadelphia – 2015

TB64 64-Room 113A, CC Panel Discusssion: A Heated Discussion on Decision Analysis and Systems Engineering Sponsor: Decision Analysis Sponsored Session Chair: Ali Abbas, Professor Of Industrial And Systems Engineering And Public Policy And Director Of Create, University of Southern California, 3710 McClintock Avenue, RTH 314, Los Angeles, CA, United States of America, aliabbas@price.usc.edu 1 - The Need for a Sound Decision Making System Moderator:Ali Abbas, Professor Of Industrial And Systems Engineering And Public Policy And Director Of Create, University of Southern California, 3710 McClintock Avenue, RTH 314, Los Angeles, CA, United States of America, aliabbas@price.usc.edu This talk reflects on some widely used methods of multi-objective decision making in both public and private enterprises, and demonstrates the issues with their use and the need for a sound decision making system. 2 - Ethical Decision Analysis Ronald Howard, Professor, Stanford University, 646 Tennyson Avenue, Palo Alto, CA, 94301, United States of America, rhoward@stanford.edu Decision analysis is inherently amoral. Like fire or nuclear energy it can be used for good or ill. The decision analyst and the decision maker have the ethical responsibility for decisions. The decision maker for the choice of action and the decision analyst as a conspirator or accomplice in clarifying what is to be done. The daily news shows the consequences of abdicating ethical responsibility. 3 - There is No Rational Framework for Systems Engineering George Hazelrigg, Deputy Division Director, National Science Foundation, Civil, Mech. & Mfg Innovation, 4201 Wilson Boulevard, Arlington, VA, 22230, United States of America, ghazelri@nsf.gov Decision analysis for systems engineering is an oxymoron. Systems engineering requires teams of people, for which decision analysis does not apply. Failure to recognize this can lead to serious problems. 4 - Decision Analysis for Systems Engineering Trade-off Analyses Greg Parnell, Professor, University of Arkansas, Department of Critical systems decisions are made throughout the system life cycle. Decision analysis offers a sound foundation for developing a composite model of complex system alternatives, major uncertainties, and stakeholder values to provide insights to systems decision makers. 5 - Decision Analysis - Towards a Theoretical Foundation of Systems Engineering and Design Chris Paredis, Program Director, National Science Foundation, 4201 Wilson Blvd, Arlington, VA, United States of America, cparedis@nsf.gov In a rapidly changing global context, out approach for engineering large-scale, complex engineered systems must also adapt quickly. A theoretical foundation for systems engineering and design is needed to help guide this adaptation in a rigorous, systematic fashion. Decision analysis is an important cornerstone of this foundation. Industrial Engineering, Fayetteville, AR, 72701, United States of America, gparnell@uark.edu

2 - How Little Do Models Tell Us? Eva Regnier, Associate Professor, Naval Postgraduate School, 699 Dyer Road, Monterey, CA, 93943, United States of America, eregnier@nps.edu, Erin Baker In arenas including weather forecasting and climate policy, simulation modeling is used to estimate uncertainty attributed to initial conditions. Model uncertainty (sometimes called structural uncertainty) is much harder to quantify. We outline a qualitative approach using Bayesian logic to answer the question: how much do model results tell us? 3 - Agile Modeling Focused on Decision Making Max Henrion, CEO, Lumina Decision Systems, Inc, 26010 Highland Way, Los Gatos, CA, 95033, United States of America, henrion@lumina.com Agile modeling borrows methods from agile software development, an alternative to the conventional approaches starting from formal requirements. Instead modelers start building a simple prototype, and refine it progressively, learning and improving as they go. Decision analysis and sensitivity analysis helps focus development on areas most decision-relevant. TB66 66-Room 113C, CC Delay Propagation and Robust Airline Operations Sponsor: Aviation Applications Sponsored Session Chair: Milind Sohoni, Associate Professor Of Operations Management And Sr. Associate Dean Of Programs, Indian School of Business, Gachibowli, Indian School of Business, Gachibowli, Hyderabad, Pl, 500032, India, milind_sohoni@isb.edu 1 - Improving Maintenance Robustness using a Route Adjustment Tail Assignment Problem Stephen Maher, Zuse Institute Berlin, Takustr. 7, Berlin, BE, 14195, Germany, maher@zib.de, Guy Desaulniers, François Soumis Maintenance planning is critical for airline operations. Daily schedule perturbations regularly prohibit aircraft from receiving maintenance as required. A robust approach employing one-day routes has been proposed, however, perturbations still affect the delivery of maintenance. A tail assignment problem that modifies routes to satisfy maintenance requirements is presented. This will demonstrate that route modifications are a necessary augmentation to a robust maintenance planning solution. 2 - Examining the Robustness of Airline Operations under Weather Disruptions Donald Richardson, University of Michigan, Ann Arbor, MI, donalric@umich.edu, Luke Stumpos, George Tam, Amy Cohn, Chhavi Chaudhry We have compiled a database containing twelve years’ worth of flight data from the Bureau of Transportation Statistics. By connecting this data with hourly National Oceanic and Atmospheric Administration weather reports, we are able to analyze how the weather affects the relationship between planned airline schedules and the actual flight performance. The purpose of this research is to provide a foundation for better understanding the robustness of airline operations under weather disruptions. 3 - Data-driven Models for Robust Aircraft Routing Lavanya Marla, Assistant Professor, University of Illinois at Urbana-Champaign, 104 S. Mathews Avenue, 216E, Urbana, IL, 61801, United States of America, lavanyam@illinois.edu, Vikrant Vaze We address the issue of pro-actively building robust aircraft routings that are less vulnerable to uncertainty, by focusing on reducing delay propagation. We present a series of data-driven models drawn from the classes of Robust Optimization and Chance-Constrained Programming that generate solutions that (i)are faithful to implicit information in the underlying data, and (ii)are less fragile to disruption. We conclude with results from a real-world airline network to provide proof-of- concept.

TB65 65-Room 113B, CC Modeling in Decision Analysis Sponsor: Decision Analysis Sponsored Session Chair: Jeffrey Keisler, University of Massachusetts Boston, 100 Morrissey Boulevard, Boston, MA, 02125, United States of America, Jeff.Keisler@umb.edu 1 - When Decision Analysis Serves to Connect a Network Jeffrey Keisler, University of Massachusetts Boston,

100 Morrissey Boulevard, Boston, MA, 02125, United States of America, Jeff.Keisler@umb.edu

An organization may wish to construct analytic models combining contributions from different experts and stakeholders in order to guide decisions. We represent this as a network of agents with reporting relationships, each with a vocabulary, a knowledge base, potential observations. Is the network rich enough to ensure the decider’s success? Recent results from mathematical logic give some answers and possible implications for decision consulting.

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