2015 Informs Annual Meeting

MD26

INFORMS Philadelphia – 2015

MD26 26-Room 403, Marriott Analytics Maturity Model Sponsor: INFORMS Practice Sponsored Session Chair: Aaron Burciaga, Analytics Executive, INFORMS Analytics Maturity Model, 4305 Majestic Ln, Fairfax, VA, 22033, United States of America, adburciaga@gmail.com 1 - The 2015 State of Analytics Report - Informs Analytics Maturity Model Aaron Burciaga, Analytics Executive, INFORMS Analytics Maturity Model, 4305 Majestic Ln, Fairfax, VA, 22033, United States of America, adburciaga@gmail.com, Paul Lima INFORMS’ members and cadre of credentialed analytics professions from across academia, business, and government now update, govern, and operate the new standard for assessing and benchmarking the application of analytics in organizations and across industries: the INFORMS Analytics Maturity Model (IAMM). During this session, the “2015 State of Analytics Report” will premier, introducing the benchmarks by industry for any organization beginning, developing, or advancing their analytics journey. MD27 27-Room 404, Marriott Spatial Multi-Criteria Decision Analysis Sponsor: Multiple Criteria Decision Making Sponsored Session Chair: Valentina Ferretti, Politecnico of Torino, Corso Castelfidardo 30/A, Torino, Italy, valentina.ferretti@polito.it 1 - Decision Analysis with Geographically Varying Outcomes Jay Simon, American University, Washington, DC, jaysimon@american.edu This work develops theory to support decisions based on data from geographic information systems (GIS). Preference conditions are introduced, leading to corresponding value and utility functions over GIS data for both single-attribute and multiple-attribute cases. These models of preferences are then applied to example decisions based on GIS data. 2 - Application of the New Gear Geospatial MCDA Tool to Humanitarian Assistance Site Selection Decisions Matthew Bates, Research Engineer, US Army Corps of Engineers, Engineer R&D Center, 696 Virginia Rd, Concord, MA, 01742, United States of America, Matthew.E.Bates@usace.army.mil, Patrick Doody, John Nedza, Erin Hughey, Richard Curran, Igor Linkov, Heather Bell, Paul Kailiponi, Michelle Hamilton Humanitarian assistance and disaster response (HADR) decisions are multifaceted, involving many stakeholders, limited funding and competing areas of need. Spatially explicit data are increasingly available to support these decisions at fine scales. We introduce GEAR, a new US-Govt-developed tool for spatial multi- criteria decision analysis that is currently being transitioned to the Pacific Disaster Center to support the HADR community. We demonstrate its application to site selection decisions. 3 - Key Challenges and Meta-choices in Designing Spatial Multi-criteria Evaluations Gilberto Montibeller, London School of Economics, Houghton Street, London WC2A 2AE, London, United Kingdom, G.Montibeller@lse.ac.uk, Valentina Ferretti Spatial multi-criteria decision analysis is being increasingly employed in environmental decision-making and in related fields. However, there are key challenges when designing such evaluations, which impose important meta- choices to decision analysts, as they may lead to different contents of the evaluation model and to distinctive outcomes of the analysis. In this paper we provide a systematic and comprehensive discussion of these key challenges and the associated meta-choices.

4 - Terrestrial Condition Assessment for National Forests of the USDA Forest Service in the Continental U.S. Keith Reynolds, Research Forester, USDA Forest Service, PNW Research Station, 3200 SW Jefferson Way, Corvallis, OR, 97331, United States of America, kreynolds@fs.fed.us, David Cleland, Barbara Schrader, Robert Vaughan The Terrestrial Condition Assessment of the National Forest System is using a spatial decision support system to assess effects of uncharacteristic stressors and disturbance agents, with an emphasis on identifying restoration opportunities at a national scale. When outcomes were classified into categories of very good, good, moderate, poor, and very poor terrestrial condition, corresponding percent areas on national forests were 9.78, 46.37, 19.22, 16.75, and 7.89%, respectively. MD28 28-Room 405, Marriott Auctions for Spectrum Cluster: Auctions Invited Session Chair: Robert Day, University of Connecticut, 2100 Hillside Road, U-1041, Storrs, CT, 06269, United States of America, Bob.Day@business.uconn.edu 1 - Optimal Bidding Strategies in Core Selecting Auctions Van Vinh Nguyen, The Fuqua School of Business, Duke University, 100 Fuqua Drive, Durham, NC, van.vinh.nguyen@duke.edu, Ozan Candogan, Sasa Pekec We analyze optimal bidding strategies of a single bidder in core selecting auctions with homogeneous items. We use robust optimization approach to formulate the bidder’s optimization problem and show that gains from non-truthful reporting are significant. 2 - Vickrey-based Pricing in Iterative First-price Auctions Oleg Baranov, University of Colorado Boulder, Boulder, CO, United States of America, oleg.baranov@colorado.edu, Lawrence Ausubel For achieving efficient outcomes in practical auction settings, an auction design should use the opportunity cost pricing principle to the extent possible to promote truthful revelation of bidder preferences, and the pricing mechanism should be implemented via an iterative “first-price” process where all bidders are fully informed about their current price at each iteration. For the heterogeneous environment with substitutes, we develop an auction design that adheres to both principles. 3 - The Use of the Clearing Target Optimization Model Within the FCC Incentive Auction We present an important component of the upcoming FCC Incentive Auction: How to choose a “clearing target”, i.e. the maximum amount of spectrum to try to buy back from broadcasters to sell to the broadband industry. A difficult combinatorial optimization problem is used to determine this target. This talk will present the formulation of this problem and our approaches to solving the problem. We also describe how this model was used to inform policy at the FCC. 4 - Multi-option Descending Clock Auction Tuomas Sandholm, Professor, Carnegie Mellon University, 5 000 Forbes Ave, Pittsburgh, PA, 15213, United States of America, sandholm@cs.cmu.edu, Tri-dung Nguyen In descending clock auctions (DCAs), bidders (sellers) can accept or reject. Yet in many settings, e.g., the FCC’s upcoming incentive auction, each bidder can sell one from a set of options. We present a DCA that offers each bidder prices for the options. We develop a Markov chain model of the dynamics of each bidder’s state, and a method for optimizing prices to offer in each round. Experiments with real FCC constraint data show it dramatically outperforms percentile-based price decrements. Karla Hoffman, Systems Eng and OR Dept., George Mason University, Fairfax, VA, 22030, United States of America, khoffman@gmu.edu, Brian Smith, Steven Charbonneau, James Costa, Tony Coudert, Steve Schmidt, Rudy Sultana

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