Optimization Toolbox 2.0

Large-Scale Algorithms

• Linear programming
• Nonlinear least squares with bound constraints
• Nonlinear system of equation solving
• Unconstrained nonlinear minimization
• Nonlinear minimization with bound constraints
• Nonlinear minimization with linear equalities
• Quadratic problems with bound constraints
• Quadratic problems with linear equalities
• Linear least squares with bound constraints

Function Names and Calling Syntax

• Command line syntax has changed:
  • Equality constraints and inequality constraints are now supplied as separate input arguments.
  • Linear constraints are supplied as separate arguments from the nonlinear constraint function.
  • The gradient of the objective is computed in the same function as the objective, rather than in a separate function, in order to provide more efficient computation (because the gradient and objective often share similar computations). Similarly, the gradient of the nonlinear constraints is computed by the (now separate) nonlinear constraint function.
  • The Hessian matrix is provided by the objective function when using the large-scale algorithms.
• Optimization parameters are now contained in a structure, with functions to create, change, and retrieve values.
• Each function returns an exit flag that denotes the termination state.