Informs 2015

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INFORMS Philadelphia – 2015
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2 - A Branch-and-Price Algorithm for Switchgrass Logistic Supply
Chain Design
Maichel M. Aguayo Bustos, Virginia Tech, 250 Durham Hall, 1145
Perry Street, MC 0118, Blacksburg, VA, 24061, United States of
America, Subhash C. Sarin, John S. Cundiff
Given the locations of a bio-energy plant and storage facilities for a switchgrass-
based bio-ethanol supply chain, we introduce a multi-period mixed integer
programming model to determine both strategic and tactical decisions. A novel
branch-and price approach is used to obtain near-optimal solutions for large-sized
problem instances. Results of its implementation to a case study are also
presented.
3 - A Newsvendor Problem with Multiple, Capacitated Suppliers and
Marginal Quantity Discounts
Roshanak Mohammadivojdan, PhD Student, University of
Florida, 303 Weil Hall, P.O. Box 116595, Gainesville, FL, 32611,
United States of America,
Joseph Geunes
We consider a newsvendor who may order stock from multiple, capacitated
suppliers, each of which offers a marginal quantity discount pricing structure. The
newsvendor seeks to minimize its total procurement plus expected overstock and
understock costs, resulting in an objective function consisting of a sum of convex
and concave terms. We provide an algorithmic approach that permits solving this
non-convex problem in pseudopolynomial time by solving a set of 0-1 knapsack
subproblems.
4 - An Integrated Model for Supplier Selection and Optimal Order
Allocation Considering Uncertainty
Majid Hooshmandi Maher, Allameh Tabatabaei University,
Faculty of Management & Accounting, Hemmat Exp, Tehran,
Iran,
This paper first presents an approach for supplier evaluation based on integrated
multiple criteria decision making model and then proposes a mathematical model
to optimize the order allocation in a supply chain considering uncertainty in
different parameters. An Iranian automobile company is utilized as a case study.
The mathematical model is solved by genetic algorithm and the performance of
the model is verified using other optimization approaches.
5 - The Production Routing Problem with Vehicle Costs
Robert Russell, Professor of Operations Management, Univ. of
Tulsa, 800 S Tucker Drive, College of Business, Tulsa, OK, 74104,
United States of America,
This paper addresses the integration of production, inventory, distribution, and
vehicle costs for supplying retail demand locations from a production facility. A
mixed integer model is used to determine an approximate solution to the
production routing problem with vehicle costs and a vehicle routing
metaheuristic is used to sequence routes for each time period. Computational
results are reported and compared to results from the traditional production
routing problem.
TD78
78-Room 301, CC
Electricity Markets and Utilities
Contributed Session
Chair: Chung-Hsiao Wang, LG&E and KU, 102 Spruce Ln, Louisville,
KY, United States of America,
1 - Analysis of Consumer Behavior Towards Dynamic Residential
Electricity Pricing
Prajwal Khadgi, PhD Candidate, University of Louisville,
Speed School of Engineering, Louisville, KY, 40219,
United States of America, Lihui Bai
Variable electricity pricing for the control of residential load has attracted much
interest in the field of demand response, and static variable pricing such as time of
use rates has had successful applications in the US as an optional service.
However, dynamic variable pricing remains an open question, due to lack of
understanding on consumer behavior. We study consumer behavior against two
dynamic rates, i.e., demand charge and load-following rates, using utility
functions and simulation.
2 - A Dynamic Garch Model for Energy Portfolio Allocation in
Electricity Markets
Reinaldo Garcia, Associate Professor, University of Brasilia - UnB,
Faculty of Technology, Industrial Engineering Department,
Brasilia, 70904-970, Brazil, , Javier Contreras,
Virginia González, Janiele E. S. C. Custodio
In the deregulated electricity markets, a Generation Company (Genco) has to
optimally allocate their energy portfolio. Modern Portfolio Theory (MPT) allows a
Genco to maximize their profit and decrease their associated risk. This paper
proposes a model where MPT is combined with a Generalized Autoregressive
Conditional Heteroskedastic (GARCH) prediction model for a Genco to optimally
diversify their energy portfolio. The model is applied to the PJM electricity market
showing its capabilities.
3 - Intraday Electricity Load Forecasting using Rule-based Model
Myung Suk Kim, Professor, Sogang University, #1 Shinsu-Dong,
Mapo-Gu, Seoul, Korea, Republic of,
A rule-based model selection methodology incorporating a multiplicative seasonal
autoregressive with exogenous variables (ARX) model and a support vector
machine (SVM) is provided and applied to Korean hourly electricity load data. We
set up a rule that determines which of the SVM and ARX models should be
applied to forecasting a specific hour within a day. The proposed rule-based model
selection methodology outperforms its benchmarks.
4 - Modeling Grid Operations in China’s Partially-Restructured
Electricity Market
Michael Davidson, Massachusetts Institute of Technology, 400
Main Street, E19-411, Cambridge, MA, 02139, United States of
America, Valerie Karplus, Ignacio Perez Arriaga
Long transitions of restructuring vertically-integrated electric utilities can affect
interim market operations and assumptions underlying tools for policy
assessment. We develop a mixed integer unit commitment model of China’s
northeast region with several legacy central planning mechanisms modeled as
regulatory constraints and penalties. We analyze their influence on system
operation, test tractability of formulations and validate with actual operational
outcomes.
5 - Fuel Hedging Strategy for Electric Power Utilities
Chung-Hsiao Wang, LG&E and KU, 102 Spruce Ln, Louisville,
KY, United States of America, ,
Kyung Jo Min
In recent years, natural gas combined cycle power plants have started to replace
aging and less efficient coal power plants. Because fuel costs represent the
majority of total costs for an electric power utility, how to manage volume and
price risks for coal and natural gas fuel is critically important. In this paper, we
develop mathematical models for structured and analytical guidelines on fuel
hedging strategies for a utility owning both types of generation units.
TD79
79-Room 302, CC
Software Demonstration
Cluster: Software Demonstrations
Invited Session
1 - SAS - Building and Solving Optimization Models with SAS
Ed Hughes, Principal Product Manager, SAS, Rob Pratt,
David Kraay
SAS provides a broad spectrum of data and analytic capabilities, including
statistics, data and text mining, econometrics and forecasting, and operations
research-optimization, simulation, and scheduling. OPTMODEL from SAS
provides a powerful and intuitive algebraic optimization modeling language and
unified support for building and solving LP, MILP, QP, NLP, CLP, and network-
oriented models. We’ll demonstrate OPTMODEL for basic and advanced
problems, highlighting its newer capabilities and its support for both standard and
customized solution approaches.
2 - Responsive Learning Technologies - Online Games to Teach
Operations and Supply Chain Management
Sam Wood, President, Responsive Learning Technologies
Learn about online competitive exercises that are used in Operations
Management courses and Supply Chain Management courses to teach topics like
capacity management, lead time management, inventory control, supply chain
design and logistics. These games are typically used as graded assignments
TD79