2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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4 - Optimal Process Adaptation For Robust Iot Collaboration
Zhe Shan, University of Cincinnati, Cincinnati, OH, Contact:
The purpose of process adaptation is to mediate the communication between sev-
eral independent IoT processes to overcome their mismatches and incompatibili-
ties. In this work, we propose a new framework and efficient algorithms for cre-
ating optimal adapters for IoT process collaboration. This solution integrates mes-
sage adaptation patterns with control flow adapters to create a complete adapter
for multiple processes. The comparisons against existing methods show that our
approach produces remarkable improvements.
MD57
Music Row 5- Omni
Influencing Behavior in Aircraft Operations
Sponsored: Behavioral Operations Management
Sponsored Session
Chair: Kenneth Schultz, Air Force Institute of Technology, 2950 Hobson
Way, WPAFB, OH, 45433, United States,
1 - Antecedents Of Fuel Efficiency
James Cotton, AFIT,
The United States Air Force (USAF) uses $15B of fuel each year, more than all
other Department of Defense agencies combined (USAF 2014, 30). USAF data
show that certain pilots fly more efficiently than their peers; however, current
literature has little research on discretionary pro-environmental professional
behaviors. We use the Theory of Planned Behavior as a starting point (Ajzen,
1985, 2011), and incorporate theory as proposed by Lülfs and Hahn (2013, 2014)
and McDonald (2014), including additional factors to more accurately capture the
behavior and context of USAF cargo pilots. The results should help us understand
pilot motivation and help us encourage more efficient vehicle operation.
2 - The Effects Of Public Versus Private Feedback On
Autonomous Motivation
Kenneth Schultz, Air Force Institute of Technology, WPAFB, OH,
Cory Sanders
Research has shown public feedback increases work performance compared to
private feedback (Song, Tucker, Murrell, and Vinson, 2015). What motivates
employees to perform differently in the two conditions is an open question. To
answer this, we can investigate the motivation type differential between the two
(Ryan and Deci, 2000). Motivation type is important because controlled motiva-
tion can result in unethical behavior (Welsh and Ordonez, 2014), lower quality
of life (Gagne, 2014), and lower task persistence (Ryan and Deci, 2000) com-
pared to autonomous motivation. We will investigate this question in a longitu-
dinal field experiment using Boeing C-17 pilots’ fuel efficiency performance.
MD58
Music Row 6- Omni
Energy VIII
Contributed Session
Chair: Carlos Abreu, Adjunct Professor, Federal University of Rio
Grande do Norte State (UFRN), Natal, Brazil,
1 - Optimal Multi-Period Energy Procurement Policies With The
Integration Of Wind Energy
Tian Wang, Huazhong University of Science and Technology,
School of Management, Hongshan Distrct, Wuhan, 430074, China,
The changes of electricity market are envisioned to be revolutionary in power
generation and consumption. How to manage the increasing potential of
adjustable demand with the increasing penetration of renewable sources is one of
the most significant problems. We investigate a multi-period energy procurement
model for a smart grid community. Multiple periods of harvesting (renewable
energy) and purchasing (traditional energy) are required for satisfying demand.
Demand can be delayed if any energy shortfall. At the end, all demand must be
fulfilled. We obtain dynamic solutions and provide numerical studies.
2 - Energy Flow Network Stochastic Optimization Through Predictive
Analytics Of Energy Demand
Ebisa Wollega, Assistant Professor, Colorado State University-
Pueblo, 2200 Bonforte Blvd, Pueblo, CO, 81001, United States,
, Hiba Baroud, Vitor Winckler
Modeling energy flow depends on a number of uncertain factors that are related
to economic development, extreme weather, and renewable energy sources
availability, among many others. In order to improve decision making under
uncertainty in the energy sector, we present a stochastic non-linear mixed integer
energy flow network model under supply uncertainty where the energy demand
is determined through data-driven statistical models. Computational results that
compare the performance of different predictive models for energy demand and
the efficiency of the solution approach will be presented.
3 - Real Time Pricing Strategies And Dynamic Load Scheduling In
Smart Communities
Vignesh Subramanian, University of South Florida, 5006,
Bordeaux Village pl, Apt #201, Tampa, FL, 33617, United States,
Tapas K. Das
Real Time pricing will actively engage the electricity consumers, having an
advanced metering infrastructure (AMI), in a centralized demand side
management (CDSM), a key to price stability and network reliability. We propose
a Quadratic Binary Programming model for a centralized controller to schedule
the consumer load. The numerical result demonstrates how CDSM can lower the
price peaks, reduce the reserve capacity of the generator and minimize the
consumer’s hourly tariff.
4 - The Effects Of Low Prices And Higher Uncertainty On Enhanced
Oil Recovery Projects: A Real Options Valuation Perspective
Carlos Abreu, Adjunct Professor, Federal University of Rio Grande
do Norte State (UFRN), Natal, Brazil,
Lielson Santos, Juli Sergine, Nayara Nagly
Real Option Valuation main objective is the financial analysis of projects under
uncertainty conditions. The Oil and Gas industry is full of uncertainties starting
with its main economic variable, oil prices. Using a Real Options model to
evaluate the potential return of an oil project captures the flexibility of a decision-
maker to capture possible prices oscillations. Enhanced oil recovery projects are
developed to try to elevate mature oil field production using injection technology.
We focus on the injection of natural gas to boost the oil production analyzing
uncertainty scenarios involving oil and gas markets to estimate a decision -
making rule for investment in a Real Option perspective.
MD60
Cumberland 2- Omni
Modeling and Analysis of Innovative Mobility
Services I
Sponsored: TSL, Urban Transportation
Sponsored Session
Chair: Yafeng Yin, University of Florida, University of Florida,
Gainesville, FL, 32611, United States,
1 - A Stable Matching Paradigm For Transport Service Allocation,
User Assignment, And Pricing
Joseph Y J Chow, New York University,
Assignment in a generic transportation system (including shared mobility options)
is modeled as a many-to-one stable matching problem of passengers to tour sets.
The result allows joint assignment of flows and mechanism design for allocation
of costs, with implications for designing fare pricing and incentives for shared
mobility, and designing for partnerships between operators in this setting.
2 - Modeling Surge Pricing In Ride Sourcing Markets
Yafeng Yin, University of Florida, Civil and Coastal Engineering,
365 Weil Hall Box 116580, Gainesville, FL, 32611, United States,
, Liteng Zha
This study proposes an equilibrium model to quantitatively investigate the effects
of surge pricing on the ride-sourcing market (e.g., Uber and Lyft). The proposed
model explicitly captures the behaviors of agents at both demand and supply
sides. Equilibrium outcomes under surging strategies with different control
objectives are compared and discussed.
3 - Is Ride-sourcing Services Worsening Traffic Congestion?
Hongyu Chen, Northwestern University, ,
Yu Nie
Ride-sourcing services which allow private car owners to provide taxi-like
services for profit, have offered passengers a convenient choice of transportation
but also created controversies. It has been argued that they might have worsened
traffic congestion by both attracting more demand for mobility services and
inducing more empty-loaded vehicles on the road network. This research aims to
analyze the personal mobility services market with both traditional taxi and ride-
sourcing services using an aggregate economic model. Various impacts of the
emerging services on the market, especially on traffic congestion, will be the focus
of this research.
MD60