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Global Optimization Toolbox Product Description

Solve multiple maxima, multiple minima, and nonsmooth optimization problems

Global Optimization Toolbox provides functions that search for global solutions to problems that contain multiple maxima or minima. Toolbox solvers include surrogate, pattern search, genetic algorithm, particle swarm, simulated annealing, multistart, and global search. You can use these solvers for optimization problems where the objective or constraint function is continuous, discontinuous, stochastic, does not possess derivatives, or includes simulations or black-box functions. For problems with multiple objectives, you can identify a Pareto front using genetic algorithm or pattern search solvers.

You can improve solver effectiveness by adjusting options and, for applicable solvers, customizing creation, update, and search functions. You can use custom data types with the genetic algorithm and simulated annealing solvers to represent problems not easily expressed with standard data types. The hybrid function option lets you improve a solution by applying a second solver after the first.

Key Features

  • Surrogate solver for problems with lengthy objective function execution times and bound constraints

  • Pattern search solvers for single and multiple objective problems with linear, nonlinear, and bound constraints

  • Genetic algorithm for problems with linear, nonlinear, bound, and integer constraints

  • Multiobjective genetic algorithm for problems with linear, nonlinear, and bound constraints

  • Particle swarm solver for bound constraints

  • Simulated annealing solver for bound constraints

  • Multistart and global search solvers for smooth problems with linear, nonlinear, and bound constraints