FICO (NYSE:FICO), a leading predictive analytics and decision management software company, announced that researchers at the Lawrence Livermore National Laboratory (LLNL), will include the FICO^® Xpress Optimisation Suite in their work to determine the lowest-cost scheduling of electric power grids. LLNL are collaborating with the Catholic University of Louvain, Belgium, to 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.”

“FICO offers the best solution for implementing parallel optimisation 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. ”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 optimisation 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.”

“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,” said Rajan, who is collaborating with the Catholic University of Louvain on the energy problem. “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.”

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 Optimisation Suite software is a platform for building optimisation solutions that drives business process improvements. The Xpress Optimisation Suite provides easy ways to create deploy and utilize business optimisation solutions based on scalable high-performance algorithms, a flexible modeling environment, and rapid application and reporting capabilities for on-premise and cloud installations.