Global Optimization Toolbox
Solve multiple maxima, multiple minima, and nonsmooth optimization problems
Plot of different types of problems Global Optimization Toolbox can solve: nonsmooth (top), single global minimum nested inside multiple local minima (left), multiple local minima with no global minimum (right).
Global Optimization Toolbox provides methods that search for global solutions to problems that contain multiple maxima or minima. It includes global search, multistart, pattern search, genetic algorithm, and simulated annealing solvers. You can use these solvers to solve optimization problems where the objective or constraint function is continuous, discontinuous, stochastic, does not possess derivatives, or includes simulations or black-box functions with undefined values for some parameter settings.
Genetic algorithm and pattern search solvers support algorithmic customization. You can create a custom genetic algorithm variant by modifying initial population and fitness scaling options or by defining parent selection, crossover, and mutation functions. You can customize pattern search by defining polling, searching, and other functions.
