Informs Annual Meeting 2017

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INFORMS Houston – 2017

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351F Directions of Service Science Journal Sponsored: Service Science Sponsored Session 1 - Directions of Service Science Journal

352C Complex Multi-criteria Decision Making Problems II Sponsored: Multiple Criteria Decision Making Sponsored Session Chair: Murat Mustafa Koksalan, Middle East Technical University, Ankara, 06531, Turkey, koksalan@metu.edu.tr Co-Chair: Banu Lokman, Middle East Technical University, Ankara, 06800, Turkey, lbanu@metu.edu.tr 1 - Interactive Approaches for Bi-objective UAV Route Planning in Continuous Space Hannan Tureci, Middle East Technical University, çi Blokları Mah. 1427.Cad. 1508.Sok., Ankara, Turkey, hannantureci@gmail.com, Murat Mustafa Koksalan, Diclehan Tezcaner Ozturk In this study, we consider the route planning problem of unmanned air vehicles (UAVs). We use two objectives; minimizing total distance traveled and minimizing total radar detection threat. We consider routing in a 2-D continuous terrain, in which we have infinitely many efficient trajectories between target pairs. We develop interactive algorithms that find the most preferred solution of a route planner, who has either of the underlying preference function structures: linear or quasiconvex. To implement the algorithms to problems, we use approximated nondominated frontiers of the trajectories between targets. We demonstrate the interactive algorithms on illustrative examples. 2 - An Interactive Approach for Product and Process Design Parameter Optimization under Model Uncertainty Melis Ozates, Middle East Technical University, Industrial Engineering Dept, Office Room 318, Ankara, 06800, Turkey, mozates@metu.edu.tr, Gulser Koksal, Murat Mustafa Koksalan We develop an interactive approach for the two-response product and process design optimization problem, considering DM’s preferences under model uncertainty. We involve the problem analyst (PA) in the searching procedure to help the DM converge to his/her preferred solutions quickly. The PA systematically searches the relevant solution space at each iteration by converting DM’s verbal preferences into mathematical expressions. 3 - Real Time Bicriteria Route Planning for Unmanned Air Vehicles Murat Mustafa Koksalan, Middle East Technical University, Industrial Engineering Department, Ankara, 06531, Turkey, koksalan@metu.edu.tr Murat Mustafa Koksalan, Georgetown University, Washington DC, DC, United States, koksalan@metu.edu.tr, Diclehan Tezcaner Ozturk, Nail Karabay Distance and threat minimization are important criteria in the route planning of unmanned air vehicles. In this study, we consider these criteria and acknowledge that the conditions keep changing during the trip. We develop an approach that keeps modifying the route in real time. We assume that the route planner has a linear value function of the two criteria which we know partially. We demonstrate the approach on several example problems. 4 - Using Bilevel Programming to Solve Multiobjective Optimization Problems Serpil Sayin, Koc University, College of Admin Sciences and Economics, Rumeli Feneri Yolu Sariyer, Istanbul, 34450, Turkey, ssayin@ku.edu.tr, Gokhan Kirlik We propose a bilevel programming formulation that is capable of delivering an efficient solution of a multiobjective optimization problem that maps into a given set, provided that one exits. If the Decision Maker’s preferences are known a priori, they can be used to specify the given set. Alternatively, the bilevel program can be used to obtain a representation of the nondominated set. This requires a thorough search of the outcome space. While building a discrete representation, the algorithm also generates an approximation of the nondominated set within the specified error factor. We illustrate the approach on a multiobjective linear programming problem and discuss its strengths and weaknesses. 5 - Interactive Evolutionary Approaches to Multi-objective Feature Selection Muberra Ozmen, University College London, Level 38, 1 Canada Square, London, E14 5AA, United Kingdom, muberra.ozmen.16@ucl.ac.uk, Gulsah Karakaya, Murat Mustafa Koksalan In feature selection problems, the aim is to select a subset of features to characterize an output of interest. In characterizing an output, we may want to consider multiple objectives such as maximizing classification performance, minimizing number of selected features or cost, etc. We develop a preference- based approach for multi-objective feature selection problems. Finding all Pareto optimal subsets may turn out to be a computationally demanding problem and we still would need to select a solution. Therefore, we develop interactive evolutionary approaches that aim to converge to a subset that is highly preferred. We test our approaches on several instances and demonstrate they work well.

Paul Maglio, University of California, Merced, 5200 N. Lake Rd, Merced, CA, 95343, United States, pmaglio@ucmerced.edu INFORMS Service Science publishes articles about various aspects of service and service systems, highlighting customer-oriented services, service operations and management, and healthcare applications of service. In this session, you will learn more about the journal and the service science community at INFORMS from the Editor-in-Chief and Area Editors and others. 2 - Panelist Seyed Iravani, Northwestern University, Department of Industrial Engineering, 2145 Sheridan Road/C210 Tech, Evanston, IL, 60208-3119, United States, s-iravani@northwestern.edu 3 - Panelist Sriram Dasu, University of Southern California, Marshall School of Business Bridge Hall 401, Data Sciences and Operations, Los Angeles, CA, 90089-0809, United States, jakeiawa@marshall.usc.edu 4 - Panelist Maria Esther Mayorga, North Carolina State University, 400 Daniels Hall, Dept. of Industrial & Systems Engineering, Raleigh, NC, 27695, United States, memayorg@ncsu.edu 352B Analytics and OR for Cloud Computing and Internet of Things (IoT) Sponsored: Service Science Sponsored Session Chair: Aly Megahed, IBM Research - Almaden, San Jose, CA, 95123, United States, aly@gatech.edu 1 - A Stochastic Programming Approach for Cloud Elasticity Aly Megahed, IBM.Research - Almaden, 150 Palm Valley Blvd Apt 2066, San Jose, CA, 95123, United States, aly.megahed@us.ibm.com, Mohamed Mohamed, Sameer Tata, Chelliah Sriskandarajah, Jon Stauffer Vertical elasticity in cloud applications is the ability of increasing or decreasing computing resources to handle incoming queries. This is commonly achieved is via increasing or decreasing deployed application instances. Determining the optimal number of instances for a given horizon is challenging, because of the random number and type of incoming queries. There is also a trade-off between deploying too many instances (paying unnecessary deployment costs) and deploying too few of them (penalties for delaying query execution). We propose a stochastic programming method for this problem. 2 - Optimizing Metric Monitoring Frequencies in Resource-constrained IoT Applications Jennifer A. Pazour, Assistant Professor, Rensselaer Polytechnic Institute, 110 8th street, CI I.5217, Troy, NY, 12180, United States, pazouj@rpi.edu, Aly Megahed, Ahmed Nazeem, Samir Tata, Mohamed Mohamed We formulate a mixed integer program to determine the optimal monitoring start time and interval frequency for multiple metrics in resource constrained Internet of Things (IoT) environments. The optimization model is used for adaptive monitoring and resolved when triggered based on monitored values or environmental events. Given solution time is critical, application-specific solution approaches are developed and tested, including reformulation, valid inequalities, and column generation procedures. 3 - Stabilizing Consumer Electrical Demand Ray Strong, IBM, San Jose, CA, United States, hrstrong@us.ibm.com, Ralphael Arar, Kevin Roche, Sandeep Gopisetty We discuss managing and stabilizing power consumption in a smartly-connected private home or office using a controlled system of IoT devices. Each IoT device is closely associated with an electrical power consuming element, a set of circuit switches, a rechargeable battery, an independent source of power, or the local connection to a public electrical power utility. Stabilizing consumption will tend to produce a win for both consumer and utility. MB37

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