global-optimization-toolbox0 pages

Global Optimization Toolbox
Solve multiple maxima, multiple minima, and nonsmooth optimization problems
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.
Key Features
▪ Interactive tools for defining and solving optimization problems and monitoring solution progress
▪ Global search and multistart solvers for finding single or multiple global optima
▪ Genetic algorithm solver that supports linear, nonlinear, and bound constraints
▪ Multiobjective genetic algorithm with Pareto-front identification, including linear and bound constraints
▪ Pattern search solver that supports linear, nonlinear, and bound constraints
▪ Simulated annealing tools that implement a random search method, with options for defining annealing
process, temperature schedule, and acceptance criteria
▪ Parallel computing support in multistart, genetic algorithm, and pattern search solvers
▪ Custom data type support in genetic algorithm, multiobjective genetic algorithm, and simulated annealing
solvers

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