Global Optimization Toolbox

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
Plot of a nonsmooth objective function (bottom) that is not easily solved using traditional gradient-based optimization techniques. The Optimization Tool (middle) shows the solution found using pattern search in Global Optimization Toolbox. Iterative results for function value and mesh size are shown in the top figure.

Plot of a nonsmooth objective function (bottom) that is not easily solved using traditional gradient-based optimization techniques. The Optimization Tool (middle) shows the solution found using pattern search in Global Optimization Toolbox. Iterative results for function value and mesh size are shown in the top figure.

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