SAN JOSE, Calif. — March 24, 2014 — FICO(NYSE:FICO), a leading predictive analytics and decision management software company, today announced that researchers at the California-based Lawrence Livermore National Laboratory (LLNL) will include the FICO® Xpress Optimization Suite in their work to determine the lowest-cost scheduling of electric power grids. This is part of the Lab’s work on large-scale renewable energy integration.
“We are researching ways to determine which power generators to operate, and how much power to produce at each generator, to meet demand for a region at the lowest cost,” said Deepak Rajan, an Operations Research expert at LLNL’s Center for Applied Scientific Computing. “Typically, this is solved at many time-scales, from long-term planning all the way down to day-ahead operations planning. Our work involves solving the ‘stochastic unit commitment problem,’ which attempts to capture the uncertainty in the system, including such weather components as temperature, wind speed, and cloud cover. This problem can be cast as an extremely large-scale mixed integer linear program — to be solved on thousands of CPU cores in parallel — which is well-suited for the FICO software.”
“FICO offers the best solution for implementing parallel optimization algorithms, which I see as a major area of industrial application and academic research,” said Anthony Papavasiliou, an assistant professor in the Center for Operations Research and Econometrics of the Catholic University of Louvain, Belgium, who is collaborating with Lawrence Livermore National Laboratory on the energy problem. ”This is due to the integrated offering of a math programming language, Mosel, that can handle processor communication for parallel algorithms, and a solver that is one of the most competitive commercial solvers in the market. My interaction with the company has been extremely positive, and they have responded immediately to even the most detailed technical questions.”
Papavasilou notes that he also uses another optimization software program, but chose Xpress for this extremely challenging work. “Running some programs in parallel in order to implement decomposition algorithms requires two layers of programming,” he said. “This introduces significant implementation inefficiencies and delays, because the two layers may be implemented in different languages, and it makes the description of a math program a tedious task. Xpress, with its integrated solution to the parallel programming of decomposition algorithms, is a better solution for this kind of problem.”
Lawrence Livermore National Laboratory’s mission is to strengthen the United States’ security through the development and application of world-class science and technology. The Lab primarily performs work for the U.S. Department of Energy’s National Nuclear Security Administration. LLNL also applies its capabilities to such challenges as energy, climate change and boosting the nation’s economic competitiveness.
FICO® Xpress Optimization Suite software is a platform for building optimization solutions that drive business process improvements. The Xpress Optimization Suite provides easy ways to create, deploy and utilize business optimization solutions based on scalable high-performance algorithms, a flexible modeling environment, and rapid application and reporting capabilities for on-premise and cloud installations.
FICO (NYSE: FICO), formerly known as Fair Isaac, is a leading analytics software company, helping businesses in 90+ countries make better decisions that drive higher levels of growth, profitability and customer satisfaction. The company’s groundbreaking use of Big Data and mathematical algorithms to predict consumer behavior has transformed entire industries. FICO provides analytics software and tools used across multiple industries to manage risk, fight fraud, build more profitable customer relationships, optimize operations and meet strict government regulations. Many of our products reach industry-wide adoption. These include the FICO® Score, the standard measure of consumer credit risk in the United States. FICO solutions leverage open-source standards and cloud computing to maximize flexibility, speed deployment and reduce costs. The company also helps millions of people manage their personal credit health.
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