2016 INFORMS Annual Meeting Program

WA71

INFORMS Nashville – 2016

WA69 Old Hickory- Omni

2 - Spatial-temporal Air Quality Mapping For Smart-in Vehicle Climate Control Management Yimin Liu, Ford Motor Company, Dearborn, MI, United States, yliu59@ford.com, Yu Chen, Jinjing Yang, Yun-Jhong Wu The proliferation of connected car technologies with App and cloud-based analytics provided opportunities for effective vehicle climate control management. To enable the technologies, we propose an advanced spatial- temporal model to forecast a high resolution air pollution map fusing existing government data with the data from vehicle external sensors. Furthermore, an optimization algorithm is developed to manage in-vehicle air quality at the optimal level during the trip via the technology. 3 - Road Pricing For Informed Users With Risk Neutral Time Cost And Risk Averse Health Cost Zhen Tan, Cornell University, 314 University Ave., Apt 7, Ithaca, NY, 14850, United States, zt78@cornell.edu We analyze tolling for road users with differentiated trip value and delay and health cost incurred by congestion. Users are informed with delay and pollutant exposure level. We assume users are risk-neutral to delay but risk-averse to toxic air inhalation. The linear delay disutility has a multiplier increasing in the trip- value, while user’s disutility function of inhalation has absolute risk-aversion decreasing in trip-value. Based on properties of steady-state volume- delay/inhalation relationships, we characterize the welfare /revenue maximizing price for one bottleneck and for one prioritized route among two. We discuss on how health information affects congestion management. 4 - Using Optimization To Improve The Freight Transportation Operations Of A Fedex Licensee Omar Ben-Ayed, Qatar University, College of Business and Economics, Doha, Qatar, omar.benayed@qu.edu.qa, Salem Hamzaoui, Leandro C Coelho We describe the applications of network design and timetabling optimization to a major freight transportation company in the MENA region in order to improve its performance in terms of cost and delivery time. The application involved two sequential projects. The first developed and implemented new design and new timetable that led to remarkable gains for the company. Later, the second project involved devising better optimization models, obtaining more accurate data, and more importantly establishing a broader cooperation with the practitioners, mostly thanks to the trust gained after the success of the first project. Again, the implementation of our results led to significant improvements. 5 - Column Generation For Vehicle Routing Problems With Synchronization Constraints Markus Matthaus Frey, Dr., Technical University Munich, Arcisstrasse 21, Munich, 80333, Germany, markus.frey@tum.de, Martin Fink, Ferdinand Kiermaier, Francois Soumis, Guy Desaulniers, Rainer Kolisch Synchronization of workers and vehicles plays a major role in many industries and belongs to the class of vehicle routing problems with multiple synchronization constraints (VRPMSs). We present a VRPMSs archetype covering all synchronization types including movement and load, and propose two mathematical formulations to efficiently model all synchronization types. Additionally, we develop a column generation approach employing a novel fixing strategy. Game Theory I Contributed Session Chair: Jian Yang, Associate Professor, Rutgers University, 1 Washington Park, Rm 1084, Newark, NJ, 7102, United States, jyang@business.rutgers.edu 1 - A Unified Framework For Vehicle Licenses Allocation Zhou Chen, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, Hong Kong, zchenaq@connect.ust.hk, Qi Qi, Changjun Wang Recently, many big cities began to adopt the vehicle licenses quantitative control policies. In these cities, a limited number of licenses are allocated every month. The current allocation policies differ from city to city. In this work, we propose to target the dual objectives of efficiency and equality and present a two-stage framework that unifies most current mechanisms and outperforms all existing mechanisms in both efficiency and equality. The unified framework also leads to easy implementation due to its truthfulness, distribution-free and highly efficiency. Furthermore, we extend our unified framework into multiple stages and fully characterize the optimal mechanism. WA71 Electric- Omni

Joint Session Telecom/MIF: Modeling and Optimization for Social Network Analysis Sponsored: Telecommunications/MIF Sponsored Session Chair: Eli Olinick, Southern Methodist University, P.O. Box 750100, Dallas, TX, 75275, United States, olinick@lyle.smu.edu 1 - Design Of Survivability Networks Under Vulnerability Constraints Luis Gouveia, University of Lisbon, legouveia@fc.ul.pt, Markus Leitner We consider the Network Design Problem with Vulnerability Constraints (NDPVC) which simultaneously addresses resilience against failures and bounds on the lengths of each communication path. We show how the new problem differs from the Hop-Constrained Survivable Network Design Problem. We explain that the reason for this difference is that hop-constrained Mengerian theorems do not hold in general. Three graph theoretical characterizations of feasible solutions to the NDPVC are derived and used to propose integer linear programming formulations that are compared in a computational study. 2 - Characterizing Cohesive Subgroups In Social Networks Zeynep Ertem, university of Texas at Austin, Austin, TX, United States, ertem@utexas.edu, Zeynep Ertem, University of Texas at Austin, Austin, TX, United States, ertem@utexas.edu, Sergiy Butenko, Alexander Veremyev, Yiming Wang Identifying closely-knit groups of entities within complex systems might reveal interesting social circles. In this talk, we first introduce a new mathematical model that corresponds to a new definition for cohesive subgroups based on a commonly used graph metric, clustering coefficient. We develop a network- clustering algorithm using this new model. Second, we develop exact and approximate algorithms for a special case of our first model, for which two classical canonical problems (i.e., maximum independent set and maximum clique) are lower bounds. 3 - The 2-club Polytope Illya Hicks, Rice University, ivhicks@rice.edu, Foad Pajouh, Balabhaskar Balasundaram Given some positive integer k, a k-club of a graph G is a subset of its vertices S such that the subgraph induced by S, say G[S], has diameter at most k. The concept of k-clubs is one of many known relaxations of the concept of cliques for graphs. The k-club model is particularly interesting from a polyhedral point of view since it does not posses the hereditary property for k values larger than one. In this talk, we explore the 2-club polytope and derive facets related to distance domination. We also present some computational results displaying the effectiveness of these new inequalities. This is joint work with Foad Pajouh and Balabhaskar Balasundaram. 4 - A Network Flow Duality Foundation For Hierarchical Cluster Analysis Eli Olinick, Southern Methodist University, olinick@lyle.smu.edu Many popular data clustering and classification techniques from the social sciences lack a rigorous foundation in graph theory and mathematical optimization even though they are often based on graph and network models of interaction and affinity. We show that a clustering method based on the fundamental graph-theoretic concept of density and implemented via a duality to network flows can produce more comprehensive and meaningful results in appropriate problem domains.

WA70 Acoustic- Omni Transportation, Ops I Contributed Session

Chair: Markus Matthaus Frey, Dr., Technical University Munich, Arcisstrasse 21, Munich, 80333, Germany, markus.frey@tum.de 1 - A Simulation-based Optimization Framework For Online Urban Traffic Control Problems Linsen Chong, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 1-245, Cambridge, MA, 02139, United States, linsenc@mit.edu, Carolina Osorio We propose an online simulation-based optimization (SO) framework that uses computationally expensive microscopic simulators for real time traffic control problems. The framework consists of a metamodel SO method, a data-fed analytical traffic model method and a data-driven method. This framework is computationally efficient and allows a high-dimensional non-linear optimization problem to be solved in real time. We illustrate the performance of the proposed method through a large-scale urban traffic responsive control case study.

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