2016 INFORMS Annual Meeting Program

445 / 561

INFORMS Nashville – 2016
445
WC57
Music Row 5- Omni
Disaster and Emergency Management II
Contributed Session
1 - Dynamic Resource Allocation For Effective Distribution Of
In Kind Donations
Merve Ozen, PhD Student, University of Wisconsin-Madison,
602 Eagle Heights, Apt I, Madison, WI, 53705, United States,
, Ananth Krishnamurthy
In the aftermath of a disaster, victim demands for relief items exceed the
immediate supply. In-kind donations sent to the affected region help reduce the
gap. In most cases, large amounts of cargo of various degrees of priority arrive at a
disaster site with in a short period of time. To sort, grade and distribute the critical
resources; prioritization and staffing decisions must be made. We model this
problem as a discrete time, discrete state space, finite horizon decision problem
where the number of resources to be dedicated to sorting operations is decided.
We investigate the structure of the optimum policies and provide managerial
insights for humanitarian organizations.
2 - Robust Ambulance Allocation Using Risk-based Metrics
Kaushik Krishnan, Graduate Research Assistant,
University of Illinois at Urbana-Champaign, Urbana, IL,
United States, , Lavanya Marla
We present robust location strategies for an ambulance fleet in order to maximize
service levels under unexpected demand patterns. Our work is motivated by the
fact that when small parts of networks incur large emergencies (modeled as a
heavy-tailed distribution), the entire system behaves in a heavy-tailed manner.
We achieve robust allocations by including risk metrics that account for tail
behavior as well as average performance. We build an efficient data-driven
algorithm that optimizes based on risk metrics. Our computations show that our
solutions account for spatiotemporal patterns and prevent the extent of delay
cascades that are typically seen in heavy-tailed arrival distributions.
3 - Identifying And Monitoring International Shipments Of Hazardous
Materials And Waste
Haibo Wang, Killam Distinguished Professorship, Texas A&M
International University, 5201 University Boulevard, Laredo, TX,
78045, United States,
This project will develop a decision support system for identifying and monitoring
international shipments of hazardous materials and waste using service-oriented
platform, and provide participants with a U.S. domestic and international cross-
border pilot program.
WC58
Music Row 6- Omni
Finance II
Contributed Session
Chair: Phillip J Lederer, Professor, University of Rochester,
Simon School of Bus Admin, Rochester, NY, 14627, United States,
1 - Toward A Firm Inefficiency Risk Factor Of Stock Returns:
Model And Empirical Analysis
Daqi Xin, PhD Student, Rensselaer Polytechnic Institute,
110 8th St, Troy, NY, 12180, United States, ,
Chanaka Edirisinghe
Relative operational inefficiency of a firm in responding to supply/demand
competition manifests in high distress risk and vulnerability to economic shocks.
A set of firm financial variables are used to compute the inefficiency, relative to its
competition, having a positive lagged correlation and negative synchronous
correlation with stock returns. The proposed new inefficiency risk factor for the
market is robust to size, value and momentum risk factors.
2 - Review And Evaluation Of Operations Capital Projects
Phillip J Lederer, Professor, University of Rochester,
Simon School of Bus Admin, Rochester, NY, 14627, United States,
A major interface between finance and operations is a firm’s capital justification
process by which are set of activities to evaluate and approve a project proposal,
and to tie the its performance to managers’ incentives. We study a principal-agent
model where the agent is a manager who designs and proposes a project and, if
approved, oversees its execution, and where the principal is general management.
A unique aspect of this research is the agent’s choice of project, its effort to
manage risk and private information project riskiness. The magnitudes of
economic losses due to mis-designed compensation structure, observability of
effort, and information asymmetry are presented.
WC59
Cumberland 1- Omni
Location of Energy-Efficient Facilities
Sponsored: TSL, Facility Logistics
Sponsored Session
Chair: Mohannad Kabli, Mississippi State Univ, MSU, Mississippi State,
MS, 39762, United States,
Co-Chair: Mohammad Marufuzzaman, Mississippi State University, PO
Box 9542, Starkville, MS, 39762, United States,
1 - Stochastic Model For Locating Multiple Type Recharging Station
Under Flow Uncertainty
Sushil Raj Poudel, PhD Candidate, Mississippi State University,
Department of Industrial & Systems Engineering, P.O. Box 9542,
Starkville, MS, 39762, United States, ,
Md Abdul Quddus, Sudipta Chowdhury,
Mohammad Marufuzzaman, Linkan Bian
This study presents a two-stage stochastic mixed-integer programming model to
formulate capacitated multiple-recharging station location problem under flow
uncertainty. We solve the problem using a hybrid decomposition algorithm
combining sample average approximation with an enhanced progressive hedging
algorithm We use Washington DC as a testing ground to visualize and validate the
modeling results. The computational experiments provide the geographical
distribution for multiple types of recharging stations to ensure the completion of
overall tours of multiple type of electric vehicles in each path.
2 - Biorefinery Location And Green Perspectives
Javier Faulin, Full Professor, Public University of Navarra, Los
Magnolios Bdg. 1st floor, Campus Arrosadia, Pamplona, 31006,
Spain, Adrian Serrano-Hernandez,
Alejandro Garcia del Valle, Javier Belloso
The concern about sustainability is gaining importance leading to seek for
renewable energy sources to reduce greenhouse gas emissions (GHG) in
transportation. Therefore, this work proposes a procedure to determine a
biorrefinery location considering its supply chain environmental impact
(including, among others, crop selection and stock policy). A Mixed Integer
Linear Programming model, coded in GAMS, was solved giving promising results.
Thus, some meaningful sensitivity analysis were run in order to have the
environmental criteria met at an affordable cost. Finally, a case study of location
of a Biorefinery in Navarre, Spain has been solved.
3 - Chance-constrained Stochastic Programming Model For Locating
Charging Stations Under Uncertainty In Green Power Availability
Sudipta Chowdhury, Mississippi State University,
, Mohannad Kabli, MD Abdul Quddus,
Mohammad Marufuzzaman
Due to the scarcity and negative consequences the use of fossil fuel brings, green
energy sources are being increasingly used as an alternative clean source of
electricity. Electric vehicles are a part of the solution, and their spread is imminent
as the technologies of batteries are advancing faster than ever. This calls for plans
that regulates the potential increase in the number of charging stations, which
will lead to an increase in the demand for electricity. This work presents a chance-
constrained stochastic programming model that plans for the expansion of
charging stations with limited power supply and chance-constrained green energy
availability.
4 - A Stochastic Programming Approach For Ev Charging Station
Expansion Plans
Mohannad Kabli, MSU, , MD Abdul Quddus,
Mohammad Marfuzzaman
This paper presents a two-stage stochastic programming model that helps making
the decisions for expanding and connecting power in anticipation the increase of
electric vehicle charging stations under demand uncertainty . We solve the model
using a hybrid algorithm that combine Sample average algorithm with an
enhanced Progressive hedging (PH) algorithm. Along with SAA and Progressive
hedging we applied some heuristics such as Rolling Horizon (RH) algorithm,
variable fixing technique to enhance the PH algorithm. We choose Washington
DC as a testing ground to visualize and validate the modeling results.
WC59