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Frontline Systems, Inc. |
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To learn more, click on Genetic Algorithms and Evolutionary Algorithms - Introduction. The Premium Solver's hybrid Evolutionary/Classical Solver finds good solutions to problems involving arbitrary Excel functions, even user-written functions. And where a "classical" nonlinear Solver would find only a locally optimal solution, this hybrid Solver will often find globally optimal -- or near-optimal solution. The hybrid Evolutionary/Classical Solver uses genetic algorithm methods such as mutation, crossover, selection and constraint repair, but it also uses deterministic, gradient-free direct search methods, classical gradient-based quasi-Newton methods, and even the Simplex method for linear subsets of the constraints. The classical methods sometimes yield rapid local improvement of a trial solution, and they also help to solve for sets of constraints. This enables the hybrid Evolutionary/Classical Solver to handle problems with many (even hundreds of) constraints, which are typically beyond the capabilities of genetic and evolutionary algorithms alone. New Population ReportThe Premium Solver also includes a new Population Report for problems solved with the Evolutionary Solver. (Click on the worksheet to see it full size.) Where the Answer Report gives you detailed information about the single "best solution" returned by the Solver, the Population Report gives you summary information about the entire population of candidate solutions maintained by the Evolutionary Solver at the end of the solution process. The Population Report can give you insight into the performance of the Evolutionary Solver as well as the characteristics of your model, and help you decide whether additional runs of the Evolutionary Solver are likely to yield even better solutions. |
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