2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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aversion assumptions. We found that, theoretically, investment should decrease
with firm revenue under specific settings and preference conditions, while
experiments suggest the reverse. We also uncover dynamics in decisions where
the setting is independent over time, counter to the theory.
2 - Incentivizing Suppliers Using Scorecard
Sina Shokoohyar, University of Texas at Dallas, 800 West Campbell
Road, Richardson, TX, Jindal School of Management, Richardson,
TX, 75080, United States, Elena
Katok, Anyan Qi
Suppliers’ scorecard is a tool for manufacturers to track suppliers’ performance.
We investigate the effectiveness of two approaches for a manufacturer to
incentivize suppliers to improve their performance based on the evaluation of
their scorecard performance, the absolute and relative approaches. Under the
absolute approach, the manufacturer provides incentive to the supplier if the
supplier reaches a targeted score. Under the relative approach, the manufacturer
incentivizes suppliers based on the suppliers’ scorecard ranking in the supplier
base. Comparing the suppliers’ resultant scores under the two approaches, we
characterize conditions on which approach is preferable.
TD58
Music Row 6- Omni
Service Science
Contributed Session
Chair: Sara Saberi, Worcester Polytechnic Institute (WPI), Washburn
Rm 217, Foisie School of Business, Worcester, MA, 01609, United
States,
1 - Server Scheduling Policies For The Queues With Abandonment
Sina Ansari, Northwestern University, McCormick School of
Engineering, 2145 Sheridan Road, Evanston, IL, 60208, United
States, , Seyed Iravani,
Laurens G Debo
We study the optimal server scheduling policy in a two-class service system with
abandonment. With the objective of minimizing the total average abandonment
cost per unit time, we characterize the optimal control policy at the server using
Markov Decision Process.
2 - A Data_driven Approach To Model Fatigue At The Workplace
Zahra Sedighi Maman, PhD Student , Research Scientist, Auburn
University, Auburn, AL, 36849, United States,
, Mohammad Ali Alamdar Yazdi, Fadel
Megahed, Lora Cavuoto
This paper presents feature selection and predictive modeling approaches for
physical workload that can improve the fatigue prediction. The goal of this feature
selection is to reduce the number of the used sensors and variables obtained from
multiple sensors. The results show that the proposed approaches perform well
both in prediction performance and more importantly in feature reduction.
4 - A Network Economic Game Theory Model Of A Service-oriented
Internet With Price And Quality Competition In Both Content And
Network Provision
Sara Saberi, Assistant Professor, Worcester Polytechnic Institute,
Foisie School of Business, 100 Institute Road, Worcester, MA,
01609, United States, , Anna B Nagurney, Tilman
Wolf
This paper develops both a basic and a general network economic game theory
model of a quality-based service-oriented Internet to study the competition
among the service providers. We derive the governing equilibrium conditions and
provide the equivalent variational inequality (VI) formulations. In order to
illustrate the modeling framework and the algorithm, we present computed
solutions to numerical examples. The results show the generality of the proposed
network economic model for a future Internet.
TD59
Cumberland 1- Omni
Green Vehicle Routing
General Session
Chair: Mesut Yavuz, University of Alabama, Box 870226, Tuscaloosa,
AL, 35487, United States,
1 - Electric Vehicle Routing Problem With Time Windows And
Multiple Charger Types
Bulent Catay, Prof., Sabanci University, FENS, Tuzla, Istanbul,
34956, Turkey, Merve Keskin
The electric vehicle charging stations may be equipped with chargers having
different power supply, power voltage, and maximum current configurations. The
type of the charger affects the recharge duration. In this study, we extend the
Electric Vehicle Routing Problem with Time Windows by allowing partial
recharges using three different charger types. The objective is to minimize total
energy costs while operating minimum number of vehicles. We formulate this
problem as a mixed integer linear program and propose a matheuristic approach
to solve it effectively. The proposed approach uses an Adaptive Large
Neighborhood Search algorithm to construct the routes and utilizes a solver to
improve them.
2 - Cost Minimization And Fleet Sizing For Multifunction Electric
Bus Fleets
Amanda Farthing, Clemson University, Clemson, SC,
United States, , Nora Harris, Robert Riggs,
Scott J. Mason
We address the unique barriers facing university campus fleet managers
considering a transition to electric bus fleets. Specifically, the logistical issues
pertaining to multifunction vehicle fleets with fixed daytime routes and nighttime
dial-a-ride service are addressed. A university vehicle fleet is analyzed in order to
integrate real-world constraints, industry perspectives, and previous optimization
research to develop a vehicle selection and fleet-sizing model that minimizes total
cost. The model considers electric vehicle and infrastructure purchases, operation
costs, and environmental benefits in this setting.
3 - The Maximum Profit Mixed-fleet Electric Vehicle Routing Problem
Isil Koyuncu, University of Alabama, Tuscaloosa, AL,
United States, , Mesut Yavuz
This talk presents a maximum profit mixed fleet electric vehicle routing problem.
A mixed fleet consists of traditional gasoline or diesel and electric vehicles.
Electric vehicles enable the fleet operator to reduce their operating costs as well as
carbon emissions. In addition, a set of customers are willing to pay a premium to
receive service by electric vehicles to reduce their supply chain carbon footprint.
We formulate the emerging problem as a mixed integer linear program, and
present a route first cluster second and a greedy algorithm as well as their
computational evaluation from our preliminary experiment.
4 - Greening Patrol Routing Via Extended-range Electric Vehicles
Mesut Yavuz, University of Alabama, ,
Burcu B Keskin, Cameron Harvey, Patrick Mitchell
This study investigates patrol routing on state highways with hybrid electric
vehicles, which operate in electric mode until battery depletion, and then switch
to the more expensive gasoline mode. We present a mixed-integer non-linear
programming formulation of the problem as well as analyze some special cases in
which the problem reduces to one of minimum cost network flow. The objective
is a weighted combination of “hot spot” coverage maximization and cost
minimization. The model is tested on real data from Alabama State Troopers.
TD60
Cumberland 2- Omni
Understanding Shared Mobility and Autonomous
Vehicles: Data, Models and Optimization
Sponsored: TSL, Urban Transportation
Sponsored Session
1 - Studying Trip Planning Behavior For Taxi Drivers
Xian-Biao Hu, Metropia, Inc., Tucson, AZ, 85718, United States,
, Song Gao
Taxi cabs account for a significant portion of traffic in megacities. However,
research on taxi driver behaviors are limited and mostly formulated to maximize
the probability of picking up or minimize search time to find next passenger. Such
myopic approach departs from the driver’s actual objective to maximize profit
over the entire operation period, and may fail to explain the search behavior
around certain hotspots with high customer demand. This research aims to bridge
this gap by studying the daily trip planning behavior for taxi drivers with the goal
of maximizing profit over the entire operation period. Numeric analysis based on
one-month taxi trajectory data will also be presented.
TD60