Optimization Toolbox
Product Description
- Introduction and Key Features
- Defining, Solving, and Assessing Optimization Problems
- Nonlinear Programming
- Multiobjective Optimization
- Nonlinear Least-Squares, Data Fitting, and Nonlinear Equations
- Linear Programming
- Quadratic Programming
- Solving Optimization Problems Using Parallel Computing
Multiobjective Optimization
Multiobjective optimization is concerned with the minimization of multiple objective functions that are subject to a set of constraints. Optimization Toolbox provides functions for solving two formulations of multiobjective optimization problems:
- The goal attainment problem involves reducing the value of a linear or nonlinear vector function to attain the goal values given in a goal vector. The relative importance of the goals is indicated using a weight vector. The goal attainment problem may also be subject to linear and nonlinear constraints.
- The minimax problem involves minimizing the worst-case value of a set of multivariate functions, possibly subject to linear and nonlinear constraints.
Optimization Toolbox transforms both types of multiobjective problems into standard constrained optimization problems and then solves them using an active-set approach.
Global Optimization Toolbox provides an additional multiobjective solver for nonsmooth problems.
Multiobjective optimization used to design a low-pass filter.
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