2016 INFORMS Annual Meeting Program

TC62

INFORMS Nashville – 2016

TC62 Cumberland 4- Omni Robust and Low Cost Airline Operations under

3 - Optimal Addition Of A New Facility To The Existing Network. Planar Continuous Demand Case Dmitry Krass, University of Toronto, Toronto, ON, Canada, krass@rotman.utoronto.ca, Jonathan Lorraine We consider the optimal addition of a new facility to a set of facilities serving continuously distributed demand under the Euclidean norm. The objective is to maximize the demand attracted to the new facility; in the case of continuously distributed demand, this is equivalent to maximizing the area of the Voronoi cell of the new facility. New computational results, as well as extensions to non- uniform demand, will be presented. Relation to the L1 norm case will be discussed. 4 - Joint Optimization Of Location And Design Of New Facilities Dmitry Krass, University of Toronto, krass@rotman.utoronto.ca, Robert Aboolian, Oded Berman We address the problem of simultaneous location and design of a network of service facilities. A novel solution approach is developed, consisting of a optimal design solution for the single facility case and a an approximation scheme for the case of multiple facilities. Computational results illustrating the efficiency of the method will be presented. TC64 Cumberland 6- Omni Multiple Criteria Decision Making Applications I Sponsored: Multiple Criteria Decision Making Sponsored Session Chair: Banu Lokman, Middle East Technical University, Ankara, Turkey, lbanu@metu.edu.tr 1 - An Interactive Approach To Design Parameter Optimization Considering Response Surface Prediction Errors Melis Ozates, Middle East Technical University, Çankaya/Ankara, 06800, Turkey, mozates@metu.edu.tr, Gulser Koksal, Murat Mustafa Koksalan An interactive approach is presented for finding parameter settings of a product or process design that allows achieving targets for two responses as well as robustness. The approach utilizes response surface models and it allows the decision maker to consider magnitude of prediction errors in choosing the design solution. 2 - Prioritization Of Military Threats For Ground Based Air Defense By Analytic Hierarchy Process Gulser Koksal, Middle East Technical University, Ankara, Turkey, koksal@metu.edu.tr, Omer Kirca, Can B. Cetin, Derya Dinler, Derya Ipek Eroglu, Gulten Gokayaz In threat evaluation and weapon assignment for ground based air defense it is aimed to make threats such as bombers and missiles ineffective with systems involving weapons and jammers. Assignment of these weapons to threats may require prioritization of the threats. In this study, a threat prioritization approach based on AHP is developed and implemented. Final weights of prioritization criteria are determined by following an iterative test and optimization approach. The approach has been effective in handling inconsistencies of decision makers, and verification and validation of results. 3 - Finding Representative Nondominated Sets For Multi-objective Integer Programs Banu Lokman, Middle East Technical University, lbanu@metu.edu.tr, Gokhan Ceyhan, Murat Mustafa Koksalan We develop algorithms to generate representative nondominated sets for multi- objective integer programs. The algorithms are designed to produce a desired number of nondominated points satisfying certain quality criteria. We show that our algorithms work well on randomly generated instances of multi-objective assignment and knapsack problems. 4 - Issues In Selecting A Representative Set For Multi-objective Integer Programs Sami Serkan Ozarik, ASELSAN, ssozarik@hotmail.com, Banu Lokman, Murat Mustafa Koksalan We observe that many alternative representative sets may satisfy existing performance measures equally well. It may be useful to develop additional performance measures to break ties. We provide various properties of such sets and discuss additional possible measures. We present some empirical results.

Uncertainty and Disruptions Sponsored: Aviation Applications Sponsored Session

Chair: Heng Chen, University of Nebraska-Lincoln, Supply Chain Management and Analytics, Lincoln, NE, 68588, United States, Supply Chain Management and Analytics 1 - Incorporating Downstream Disruptions In Robust Planning And Recovery Jeremy Castaing, PhD Student, University of Michigan, 1205 Beal Avenue, 2753 IOE Building, Ann Arbor, MI, 48109-2117, United States, jctg@umich.edu, Amy Cohn When disruptions occurs in the network, airlines have to make recovery decisions to recover and minimize future cancellations, delays, passenger missed connections etc... These decisions are often made solely based on the current state of the system. We propose a robust recovery approach that takes into account correlation and propagation of delays to mitigate future disruptions. 2 - Lower Cost Airport Departure Operations Under The Departure Metering Concept Heng Chen, Assistant Professor, University of Nebraska–Lincoln, Lincoln, NE, 68588, United States, heng@unl.edu, Senay Solak Departure metering is an airport surface management procedure that limits the number of aircraft on the runway by holding aircraft at gates or at a predesigned metering area. We develop a stochastic dynamic programming framework to identify the optimal gate, metering area and departure queue allocation policies to minimize expected overall fuel burn costs. In addition, we introduce easy-to- implement practical departure metering policies and evaluate their performances. We also identify the optimal metering area capacity and quantify the value of the presence of a departure metering area at airports. 3 - On The Competition Intensity Of U.S. Airline Market With Fuel Cost Fluctuations Soheil Sibdari, University of Massachusetts, Charlton College of Business,, Dartmouth, MA, 0, United States, ssibdari@umassd.edu We investigate a recent phenomenon in the U.S. airline market that despite lower jet fuel costs, which is a major part of airlines’ operational cost, airline customers are experiencing higher airfares and more crowded planes. This can be, in part, due to the recent policies of airlines in selecting airplane sizes that changes the competition intensity. In this paper, we analyze the operations of seven major airlines including two low cost carriers and measure the impact of fuel cost fluctuations in capacity choice and competition intensity. TC63 Cumberland 5- Omni Location Analysis I Sponsored: Location Analysis Sponsored Session Chair: Dmitry Krass, University of Toronto, 105 St. George Street, Toronto, ON, M5S 3E6, Canada, krass@rotman.utoronto.ca 1 - Random Attractiveness Level In Huff’s Competitive Model Tammy Drezner, California State University-Fullerton, Steven G. Mihaylo College of Business and Economics, 800 N State College, Fullerton, CA, 92834, United States, tdrezner@fullerton.edu, Dawit Zerom, Zvi Drezner We investigate the Huff competitive location model assuming that the attractiveness level is normally distributed. It is realistic to assume that different consumers have a different perception of the attractiveness level. The model becomes the standard model when the standard deviation of the normal distribution for all facilities vanishes. We investigate the effect on the market share captured by the new facility and its optimal location by increasing the standard deviation of the new facility and/or the existing facilities. 2 - An Alternative Solution For The Time-difference-of Arrival (TDOA) Location Problem Lin Dearing, Clemson University, 520 Bentbrook Lane, Clemson, SC, 29631, United States, pmdrn@clemson.edu The TDOA location problem is to locate the source of a signal using the known locations of a set of receivers and the arrival times of a signal sent from the source to the receivers. A new approach for intersecting n-dimensional hyperboloids gives the location.

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