Informs 2015

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INFORMS Philadelphia – 2015
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2 - Analytical Stochastic Link Transmission Model Suitable for
Large-scale Analysis
Jing Lu, Massachusetts Institute of Technology, Cambridge, MA,
United States of , Carolina Osorio
We formulate a model that builds upon the previously formulated analytical
stochastic network loading model of Osorio and Flotterod (2013). The proposed
model has a complexity that is linear, rather than cubic, in the space capacity of
the links in the network. It is a scalable approach suitable for large-scale network
analysis. The model is validated versus stochastic simulation results, and is then
used to analyze a network with intricate network dynamics.
3 - A Graph-based Approach to Measure the Efficiency of Urban
Taxi Service System
Xianyuan Zhan, PhD Candidate, Purdue University, 550 Stadium
Mall Drive, School of Civil Engineering, West Lafayette, IN,
47906, United States of America, ,
Xinwu Qian, Satish V. Ukkusuri
This study investigates the efficiency level of the taxi service system using real
world large-scale taxi trip data from New York City. Two large-scale optimization
problems are formulated and transformed into equivalent graph problems to find
the theoretical optimal strategy that minimizes the cost of vacant trips, and results
in minimum number of taxis required to satisfy all observed trips. Huge
performance gap is observed between current system and the optimal system,
which suggests the potential gain by sharing system-wide information among taxi
drivers and passengers.
4 - Combining Data-driven and Model-driven Approaches for Traffic
Simulator Calibration Problems
Kevin Zhang ,Massachusetts Institute of Technology, Cambridge
MA, United States of America,
In this presentation, we approach the problem of parameter calibration of
stochastic traffic simulators through the use of Kalman filtering. We build upon
an established Kalman filtering approach by incorporating network-specific
structural information supplied by an analytical queueing model. The approach is
benchmarked versus other traditional calibration methods. Results on low-
dimensional calibration problems are presented.
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69-Room 201C, CC
Real-Time Traffic Monitoring and Control
Sponsor: TSL/Intelligent Transportation Systems (ITS)
Sponsored Session
Chair: Xuan Di, University of Michigan, Ann Arbor, MI,
United State of America,
1 - Psychological Benefits of Real-Time Travel Information on Route
Choice Behavior – Analysis of Interactive Driving Simulator
Experiment Data
Dong Yoon Song, Purdue University, West Lafayette, IN,
United States of America, , Srinivas Peeta
This study proposes a comprehensive framework to understand the psychological
mechanisms associated with real-time travel information provided. A structural
equation model with latent variables is presented to address the driver’s
psychological processes associated with real-time information based on revealed
preference data from interactive driving simulator experiments and the associated
survey data. Insights from the interactive driving simulator experiments will also
be discussed.
2 - Determining Optimal Toll Gantry Locations on Tollway
Ruoyu Liu, CDM Smith, 8140 Walnut Hill Ln # 1000, Dallas, TX,
United States of America, ,
Worapong Hirunyanitiwattana
Toll Gantry Locations can affect traffic flow and toll revenue on tollway. The
model maximizes toll revenue and also minimizes the travel cost. Genetic
algorithm is used to search the optimal solution based on result from a traffic
assignment model.
3 - Real-Time Lane-Based Traffic State Estimation and Prediction
Kerem Demirtas, Arizona State University, Tucson, AZ,
United States of America, ,
Pitu Mirchandani, Xuesong Zhou
Given new lane-based ITS applications such as speed controls and managed lanes,
one needs to estimate and predict the state of the traffic in each lane of a
highway. Based on Newell’s 1993 Simplified Kinematic Wave Model, and the p-
detector interpretation of Daganzo, we have an approach to estimate past
trajectories from Lagrangian flow-density measurements and subsequently predict
short-term trajectories using simplified behavior models. Analysis using real and
simulated data is discussed.
4 - Desirability Measures and Discovery Analysis for Multi-Modal
Services Based on Daily Trajectory Pattern Data
Yi-Chang Chiu, University of Arizona, Tuscon, AZ,
United States of America, , Ali Arian
This talk focuses on presenting a computational method to estimate the
desirability measures for various transportation modes available to a traveler
based on known multi-day daily GPS trajectory pattern data. Algorithmic details
and case studies are presented.
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70-Room 202A, CC
Vehicle Routing III
Contributed Session
Chair: Alexander Düge, TU München, Arcisstr. 21, München, Germany,
1 - Appointment Scheduling with Multiple Providers and Stochastic
Service Times
Mohamad Soltani, University of Alberta, PhD Office, Business
Building, Edmonton, AB, T6G 2R3, Canada,
Michele Samorani, Bora Kolfal
We consider a multi-server appointment scheduling problem in which patients
may not show up, and those who show up require stochastic service times. We
model this problem to evaluate each candidate solution. We statistically find some
properties for the optimal or near optimal solutions, and design a simulation
optimization approach using these properties. We also propose a heuristic
algorithm, and validate its performance by comparing its result with our
simulation optimization approach.
2 - Exact Optimization Frameworks for Time-consistent Routing
Anirudh Subramanyam, Graduate Student, Carnegie Mellon
University, DH3122, 5000 Forbes Ave, Pittsburgh, PA, 15213,
United States of America,
Chrysanthos Gounaris
We present exact approaches for the Consistent Traveling Salesman Problem,
wherein arrival-time consistency across multiple periods is enforced for each
customer. Our first approach is based on branch-and-cut. We compare alternative
formulations and propose new valid inequalities. Our second approach is based
on decomposition into single-period TSPTWs, where consistency is enforced by
tightening the windows during the search. We compare our approaches on
benchmark instances derived from TSPLIB.
3 - Rollout Algorithm for The Dynamic Vehicle Routing Problem
In City Logistics
Gitae Kim, Assistant Professor, Hanbat National University, N4 -
207, 125 Dongseo-daero, Yuseong-gu, Daejeon, 305-719, Korea,
Republic of, , Yew Soon Ong,
Taesu Cheong
This paper suggests a dynamic vehicle routing problem (DVRP) model in city
logistics. Depending on the traffic conditions, the travel time between two nodes,
particularly in a city, changes both dynamically and stochastically over time. In
this paper, we propose a Markov decision process (MDP) model for the DVRP
with the travel time dynamics under traffic congestion in the city area and adopt
the rollout algorithm to solve the problem.
4 - Vehicle Routing with Flexible Delivery Locations
Alexander Düge, TU München, Arcisstr. 21, München, Germany,
, Daniel Gartner, Markus M. Frey
We present a new extension of the vehicle routing problem (VRP): The VRP with
flexible delivery locations and time points (VRPFLTP). In the VRPFLTP, a customer
not only corresponds to exactly one location but has to be served at one out of a
set of possible capacitated locations. We develop an adaptive large neighborhood
search which demonstrates high quality solutions within short computation
times. In†our economic analysis, we trade off location flexibility on a†variety of
performance metrics.
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