Hybrid Evolutionary Solver
The hybrid Evolutionary Solver integrated with the Large-Scale SQP Solver allows you to solve non-smooth optimization problems -- for example using IF, CHOOSE or LOOKUP functions -- that cannot be handled effectively by the standard Excel Solver. It also handles integer variables and the "alldifferent" constraint.
But this Solver is much more than a genetic or evolutionary algorithm -- it also uses the SQP Solver's smooth nonlinear optimization methods to solve for constraints and improve local solutions. The result is breakthrough performance, better than virtually any genetic or evolutionary algorithm alone.
To learn more, click on Genetic Algorithms and Evolutionary Algorithms - Introduction.
The Large-Scale SQP Solver's integrated hybrid Evolutionary 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 Solver uses genetic algorithm methods such as mutation, crossover, selection and constraint repair, but it also the full power of the large-scale SQP method for local searches, when a new best point is found. The SQP method sometimes yield rapid local improvement of a trial solution, and it also helps to solve for sets of constraints. This enables the hybrid Evolutionary Solver to handle problems with many (even hundreds of) constraints, which are typically beyond the capabilities of genetic and evolutionary algorithms alone.