2015 Informs Annual Meeting

TD79

INFORMS Philadelphia – 2015

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, maiaguay@vt.edu, 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, rmohammadivojdan@ufl.edu, 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, majidhooshmand@gmail.com 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, rrussell@utulsa.edu 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, chunghsiao@hotmail.com 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, p0khad01@louisville.edu, 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, rcgarcia@unb.br, 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, myungkim@sogang.ac.kr 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, michd@mit.edu, 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, chunghsiao@hotmail.com, 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. 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 79-Room 302, CC

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