Sunday

SB48
3 - Intersection Signal Optimization using Queue Length Estimation
Yang Cheng, Research Associate, University of Wisconsin-Madison,
2204 Engineering Hall, Madison, WI, 53706, United States of
America, cheng8@wisc.edu, Jeff Ban, Bin Ran
By modern traffic detection technologies, traffic condition data would have higher
resolution in time and space, which is especially valuable for the interrupted
traffic on signalized intersections. The queue length can be estimated more easily
and accurately. Therefore, this study proposes a new signal control optimization
method based on queue information to improve corridor coordination. The
simulation results indicate that this approach has better performance than
traditional control methods.
4 - An Optimal Lane-based Signal Merge Control Model for
Freeway Work Zone Operations
Yue Liu, University of Wisconsin-Milwaukee, P.O. Box 784,
Milwaukee, WI, 53201, United States of America,
liu28@uwm.edu, Jing Mao
This paper presents a dynamic control model for optimizing lane-based signal
merge (LBSM) operations at freeway work zones. The control objective is to
maximize the throughput. GA is employed to solve the model. Results reveal that
the proposed method yields much better performance than traditional merge
strategies under heavy traffic conditions.
■ SB48
48- North 231 A- CC
Integrated Supply Chain Design
Sponsor: Transportation Science & Logistics/ Freight Transportation
& Logistics
Sponsored Session
Chair: Maged Dessouky, Professor, University of Southern California,
University Park Campus, Los Angeles, CA, 90007,
United States of America, maged@usc.edu
1 - Near-optimal Transportation and Fair Cost Allocation in an
Agricultural Supply Chain with Perishable Products
Christine Nguyen, University of Southern California,
Los Angeles, CA, United States of America, nguyen7@usc.edu,
Alejandro Toriello, Maged Dessouky
We consider an agricultural supply chain where several suppliers consolidate
transportation of a perishable product to achieve economies of scale. Using
industry data from California flower growers, we compare a practical greedy onestep
lookahead policy against optimal solutions computed from a dynamic
program, and determine whether transportation costs can be allocated fairly
among the suppliers.
2 - Integrated Supply Chain Network Design: Location,
Transportation, Routing and Inventory Decisions
Mingjun Xia, Arizona State University, 1718 S Jentilly Lane,
APT 204, Tempe, AZ, 85281, United States of America,
Mingjun.Xia@asu.edu, Ronald Askin
We propose a novel model to simultaneously optimize location, allocation,
transportation, inventory and routing decisions in a stochastic multi-product
supply chain system. Each producer provides a unique product. Each retailer has
independent, random demand for multiple products. Consolidation and
distribution facilities may be constructed to reduce shipment costs and increase
the frequency of economical shipments. Heuristics are developed to solve largesize
scale instances of the problem.
3 - Integrated Planning of Supply Chain Layout and Transportation
Infrastructure Rehabilitations
Leila Hajibabai, University of Illinois at Urbana-Champaign, 205 N
Mathews Avenue, Room 3142, Urbana, IL, 61801, United States of
America, leila.hajibabai@gmail.com, Yun Bai, Yanfeng Ouyang
Expansion of supply chains induces considerable freight shipments between
supply/demand points and intermediate facilities, which significantly accelerate
highway pavement deterioration. This paper presents an analytical method to
simultaneously design the supply chain as well as the pavement rehabilitation
plans, which determines the optimum number and location of facilities, shipment
routes, and pavement rehabilitation intensity and frequency.
4 - A Production Function-Based Empirical Analysis of Distribution
Networks
Donald Warsing, Associate Professor, North Carolina State
University, 2346 Nelson Hall, Raleigh, NC, 27695, United States of
America, don_warsing@ncsu.edu, Michael Kay, Christian Rossetti
Using a number of public data sources, we compare distribution networks in the
continental U.S. across several industry sectors. We gather data on, and/or
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compute from base-level data, a number of independent variables that we use as
inputs to a cost function for each DC in each industry data set. This cost function
serves as an important means of analyzing the variance in the input data and cost
data. We present insights regarding differences in distribution strategies across
industries.
5 - Designing LTL Load Plans to Mitigate Impact of Transit
Time Variability
Yu Zhang, PhD Student, Georgia Institute of Technology,
765 Ferst Dr NW, Atlanta, GA, 30339, United States of America,
zhangyu@gatech.edu, Alan Erera
We develop a method to design robust load plans for LTL carriers in order to
mitigate the cost impacts of transit time variability. Load plan candidates are
generated based on optimizing operations assuming that transit times take
expected values, and then evaluated and refined by Monte Carlo simulation. The
proposed method is applied to a case study which is built based on terminal and
shipment data from a national LTL carrier.
■ SB49
49- North 231 B- CC
Joint Session TSL/SPPSN: Networks and
Emergency Response
Sponsor: Transportation Science & Logistics & Public Programs,
Service and Needs
Sponsored Session
Chair: Halit Uster, Industrial and Systems Engineering, Texas A&M
University, College Station, TX, United States of America,
uster@tamu.edu
1 - A Multi-objective Integrated Approach for Emergency
Response Network Design
Jyotirmoy Dalal, Texas A&M University, 3131 TAMU, College
Station, TX, 77843, United States of America,
jyotirmoy.dalal@gmail.com, Halit Uster
We consider an emergency response network design problem to determine supply
locations and flows required in a large scale evacuation setting. We develop a
multi-objective optimization model with generalized cost structures and
proximity requirements. We present an epsilon-Costraint based approach for
generating the efficient frontier and the computational results, demonstrating the
efficiency of the method.
2 - Network Design for Emergency Response
Jianing Zhi, University of Alabama, 300 Alston Hall, Tuscaloosa,
AL, 35487, United States of America, jzhi@crimson.ua.edu,
Burcu Keskin, Sharif Melouk
We investigate a multi-period ambulance location planning problem to minimize
total cost while maintaining acceptable response times. The network consists of
supply centers, responder and incident locations, and hospitals. We propose two
models: 1) all incidents require service in the period in which they occur, and 2)
incident servicing delays are allowed but with penalty. Through experimentation,
we compare these two models in terms of service quality, response time, and cost.
3 - Resilience in Passenger Transportation Networks
Reza Faturechi, PhD Candidate, University of Maryland, 1173
Glenn L. Martin Hall, College Park, MD, 20742, United States of
America, reza@umd.edu, Elise Miller-Hooks
A bi-level stochastic program with equilibrium constraints is presented for
assessing and optimizing resilience of passenger transportation networks. At the
upper level, preparedness actions are taken to enhance the network or facilitate
response actions, and response actions are taken post-disaster to restore system
capacity. At the lower level, a partial user equilibrium is sought in which
passengers choose their routes to minimize travel time given post-disaster system
performance.
4 - Logistics Planning for Restoration of Network Connectivity
After a Disaster
Sibel Salman, Koc University, Rumeli Feneri Yolu, Sariyer,
Istanbul, 34450, Turkey, ssalman@ku.edu.tr, Ayse Nur Kibar
After a disaster, damaged roads should be repaired/unblocked by a fleet of
machinery initially positioned in a depot to restore highway connectivity. We
define a selective arc routing problem to find the walk of k vehicles with
minimum time to reach connectivity. We provide a flow-based mixed integer
programming model. We consider Istanbul’s highway and determine the number
of machinery and their initial locations under different road damage scenarios for
earthquake preparedness.