Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

TA35

3 - Provably High-quality Solutions for the Meal Delivery Routing Problem Baris Yildiz, Asst.Prof., Koc University, Rumeli Feneri Yolu, Sariyer, Istanbul, 34450, Turkey, Martin W. P. Savelsbergh Meal delivery is arguably the ultimate challenge in last mile logistics: a typical order is expected to be delivered within an hour (much less if possible), and within minutes of the food becoming ready. We introduce a novel formulation for a meal delivery routing problem in which we assume perfect information about order arrivals, and develop a simultaneous column and row generation method for its solution. The analysis of our extensive computational study, using instances derived from real-life data, demonstrates the efficacy of the solution approach, and provides valuable insights into, among others, the (potential) benefits of Iman Dayarian, Culverhouse College of Commerce, The University of Alabama, Box 870226, Tuscaloosa, AL, 35487, United States, Adolfo Antonio Rocco Rocco, Martin W. P. Savelsbergh We consider data-driven design of an intra-city logistics service network of an express courier company, offering same- and next-day delivery services. The system is designed on a multi-layer network. At the lowest level, the couriers are responsible for pick-up and delivery of the packages at the customer locations. In an intermediate level network, the riders are responsible for transferring packages between couriers and local hubs where, the shipments are sorted, consolidated, and transferred to their destination local hubs through a network of shuttles. Our goal is to design shuttle routes and schedules that guarantee on-time delivery of same-day packages, given the dynamic nature of demand. n TA33 North Bldg 222C Advances in Traffic Flow Modeling Sponsored: TSL/Intelligent Transportation Systems (ITS) Sponsored Session Chair: Dianchao Lin, New York University, New York University, New York, NY, United States 1 - A Car Following Model Incorporating Reaction Time Dynamics Online Calibration and Case Study Kerem Demirtas, Arizona State University, 699 S. Mill Ave. Tempe, Brickyard Engineering 553, Tempe, AZ, 85281, United States, Pitu B. Mirchandani, Xuesong Zhou In this study, we are interested in online calibration of car following parameters to explore both inter-driver and intra-driver heterogeneity. Specifically, we offer an augmented state space system for a lower order linear spacing car following model, and implement a modified Kalman filter algorithm to track the leader- follower pairs and simultaneously predict and estimate the parameters related with the behavior of the followers. Three different state transition models are proposed which incorporate reaction time dynamics exploiting instantaneous local density information. Comparison and interpretation of the results, and promising future research directions are given. 2 - Modeling Flood Dynamics: Interacting Processes between Transportation and Water Networks Cesar N. Yahia, The University of Texas at Austin, Austin, TX, 78705, United States, Isha Deo, Stephen D. Boyles, Paola Passalacqua We model real-time flood dynamics by considering the influence of hydrologic terrain and processes on the transportation network. We propose a data-driven model that integrates information from multiple sensors. This enables short range predictions on the disruption state of the transportation network. 3 - Stochastic Fluid Queuing Model for Evaluating Smart Highway Operations Li Jin, Assistant Professor, New York University, Brooklyn, NY, United States, Saurabh Amin, Patrick Jaillet We present a stochastic, finite-buffer fluid queuing model of serially connected highway segments that serve a mix of normal traffic and connected vehicle platoons. The queuing dynamics is governed by a Markov chain, which models capacity perturbations (due to incidents), and/or randomness in platoon integration. We derive a necessary condition and a sufficient condition for the stability of this system, and analyze the sensitivity of expected throughput under various operational scenarios. Our analysis provides novel insights for incident management and vehicle platooning operations. 4 - Lane-change Strategies for Connected Vehicles Using Cooperative Game Theory Dianchao Lin, Ph.D Candidate, New York University, New York, NY, United States, Li Li, Saif Eddin G. Jabari This paper proposes two new lane changing strategies to serve connected vehicles using cooperative game theory: transferable utility strategy which allows vehicles to transact lane usage timely using transferable utility solution, and the non- transferable utility strategy using Nash bargaining solution. Simulations using order bundling, courier shift scheduling, and demand management. 4 - Shuttle Scheduling for Same-day Courier Service

Cellular Automata are employed to explore the impact of transaction vehicles percentage, traffic density and value of time. Results showed that, cooperation between drivers could help achieve win-win result. Besides, a properly designed utility function could encourage vehicles to participate in transactions, and prevent them from cheating in their value of time. n TA34 North Bldg 223 7:30 - 8:15 Mem Computing Inc./ 8:15 - 9:00 Palisade Vendor Demo Session 1 - Overview of MemComputing Inc. Mem Computing, Mem Computing Inc., La Jolla, CA, United States Companies in all industries are seeking to optimize the efficiencies of their business environments in order to stay competitive. Data science is now coming to the forefront across departments as they seek ways to leverage big data collections to implement solutions for improved efficiency and profitability. There are a set of problems associated with optimization, big data analytics and operations research among other areas, where companies are having to accept less than the optimal answer. The challenge lies within the fact that the size and complexity of the problems will grow exponentially as the inputs and constraints grow linearly. To find viable solutions, alternative methods are employed such as reducing the amount of data analyzed, breaking the problem up into smaller problems or accepting an incomplete answer when time reaches the threshold. This is not advantageous nor is it economical as efficiencies, innovations and revenues decline.This tutorial presents a novel coprocessing architecture that is shifting the computing paradigm. Based on novel technology developed by MemComputing, Inc. its MemCPU Coprocessor platform speeds up computational time solving and finding accurate solutions for complex optimization and combinatorial problems of high economic value. 2 - Quantitative Risk Analysis in Excel with @RISK Jos Ra·l Castro, Palisade Trainer/Consultant, Palisade Corporation, Ithaca, NY, United States This tutorial will guide you in the use of @RISK for analyzing historical data and making better decisions in an uncertain business environment. @RISK is part of Palisade’s Decision Tools Suite and runs as an add-in for MS Excel. It provides all the features you need to quantify and understand risks with the support of Monte Carlo Simulation, including graphical capabilities and quick reports to help you present results to a non-technical audience. n TA35 North Bldg 224A Joint Session AAS/Practice Curated: UAS Applications and Optimization Sponsored: Aviation Applications Sponsored Session Chair: Maga Khachatryan, MagAnalytics, 3883 Park Place Estates Dr., Bridgeton, MO, 63044, United States 1 - Optimization of Grid Coverage Operations in Flight Aerial Imagery Data Collection Maga Khachatryan, MagAnalytics, St. Louis, MO, United States, Ara Nefian, Naira Hovakimyan Today, we live in the age of digital revolution which impacts modern agriculture. Every season farmers cultivate millions of acres leveraging technologies such as IoT, drones and satellites. Along with benefits technology also brings challenges. Particularly, cost of aerial imagery throughout growing season can be very high. One of the most common imagery delivery methods are airplanes. Here we describe two-stage airplane routing problem with business constrains. First stage reduces the solution space by generating flight patterns to allow faster second- stage optimization. The second stage optimizes airplane flight schedule by selecting most profitable patterns to fly over farming area. 2 - Opportunities and Challenges of Integrating UAS in the US Dipasis Bhadra, Economist, Federal Aviation Administration, 800 Independence Avenue 935-937, Washington, DC, 20591, United States, Michael Lukacs UAS has become one of the most vibrant sector of the economy in the US. With over a million registered owners/operators, the sector holds promises that span over commercial applications of numerous types to personal recreational uses. While the challenges are many, the FAA has launched various initiatives ranging from pilot programs to regulatory reforms integrating UAS into NAS. An active research program undertaken by the Agency facilitates these activities ensuring safe integration of UAS into the National Airspace System (NAS). This presentation will broadly touch on Agency’s outlook of the future, activities that are presently undertaken and the challenges/opportunities that lie ahead.

255