Problem-Based Optimization Setup

Create optimization variables, create problem with objective and constraints, callsolve

Global Optimization Toolboxhas two approaches for optimization: problem-based and solver-based. SeeDecide Between Problem-Based and Solver-Based Approach. In problem-based optimization, you create symbolic-style optimization variables. Then you create expressions in these variables that represent the objective and constraints. Finally, solve the problem usingsolve. For details, seeProblem-Based Optimization Workflow.

Note:If you have a nonlinear function that is not composed of polynomials, rational expressions, and elementary functions such asexp, then convert the function to an optimization expression by usingfcn2optimexpr. SeeConvert Nonlinear Function to Optimization ExpressionandSupported Operations for Optimization Variables and Expressions.

For a basic example, seeCompare Several Global Solvers, Problem-Based.

Functions

expand all

Create Variables and Problem

`optimproblem`	Create optimization problem
`optimvalues`	Create values for optimization problem
`optimvar`	Create optimization variables
`show`	Display information about optimization object
`showbounds`	Display variable bounds
`write`	Save optimization object description
`writebounds`	Save description of variable bounds

Create Expressions, Constraints, and Equations

`fcn2optimexpr`	Convert function to optimization expression
`optimconstr`	Create empty optimization constraint array
`optimeq`	Create empty optimization equality array
`optimineq`	Create empty optimization inequality array
`optimexpr`	Create empty optimization expression array
`show`	Display information about optimization object
`write`	Save optimization object description

Solve and Analyze

`evaluate`	评估优化表达式
`findindex`	Find numeric index equivalents of named index variables
`infeasibility`	Constraint violation at a point
`prob2struct`	Convert optimization problem or equation problem to solver form
`show`	Display information about optimization object
`solve`	Solve optimization problem or equation problem
`varindex`	Map problem variables to solver-based variable index
`write`	Save optimization object description

Objects

`OptimizationConstraint`	Optimization constraints
`OptimizationEquality`	Equalities and equality constraints
`OptimizationExpression`	Arithmetic or functional expression in terms of optimization variables
`OptimizationInequality`	Inequality constraints
`OptimizationProblem`	Optimization problem
`OptimizationValues`	Values for optimization problems
`OptimizationVariable`	Variable for optimization

Topics

Problem-Based Steps

Problem-Based Optimization Workflow
Learn the problem-based steps for solving optimization problems.
Optimization Expressions
Define expressions for both the objective and constraints.
Pass Extra Parameters in Problem-Based Approach
Pass extra parameters, data, or fixed variables in the problem-based approach.
Named Index for Optimization Variables
Create and work with named indices for variables.
Review or Modify Optimization Problems
Review or modify problem elements such as variables and constraints.
Examine Optimization Solution
Evaluate the solution and its quality.

Steps for Global Solvers

Decide Between Problem-Based and Solver-Based Approach
空洞e considerations for problem-based and solver-based optimization withGlobal Optimization Toolboxsolvers.
Global Optimization Toolbox Default Solvers and Problem Types
Identify the types of problems you can solve in the problem-based approach and their associated default solvers.
Initial Points for Global Optimization Toolbox Solvers
Specify initial points forGlobal Optimization Toolboxsolvers in the problem-based approach.
Integer Constraints in Nonlinear Problem-Based Optimization
Learn how the problem-based optimization functionsprob2structandsolvehandle integer constraints.

Set Options

Set Options
Set optimization options
Set Options in Problem-Based Approach Using varindex
To set options in some contexts, map problem-based variables to solver-based usingvarindex.
Pattern Search Options
空洞e the options for pattern search.
Genetic Algorithm Options
空洞e the options for the genetic algorithm.
Particle Swarm Options
空洞e the options for particle swarm.
Surrogate Optimization Options
空洞e the options for surrogate optimization, including algorithm control, stopping criteria, command-line display, and output and plot functions.
Simulated Annealing Options
空洞e the options for simulated annealing.

Tips for Problem-Based Optimization

Create Efficient Optimization Problems
Obtain a faster or more accurate solution when the problem has integer constraints, and avoid loops when creating a problem.
Separate Optimization Model from Data
Create reusable, scalable problems by separating the model from the data.
Variables with Duplicate Names Disallowed
Learn how to solve a problem that has two optimization variables with the same name.
Create Initial Point for Optimization with Named Index Variables
Create initial points forsolve当问题通过索引变量使用g thefindindexfunction.
Expression Contains Inf or NaN
Optimization expressions containingInforNaNcannot be displayed, and can cause unexpected results.
Objective and Constraints Having a Common Function in Serial or Parallel, Problem-Based
Save time when the objective and nonlinear constraint functions share common computations in the problem-based approach.
Obtain Generated Function Details
Find the values of extra parameters in nonlinear functions created byprob2struct.
Output Function for Problem-Based Optimization
Use an output function in the problem-based approach to record iteration history and to make a custom plot.

Parallel Computing

How Solvers Compute in Parallel
Learn how solvers distribute work for parallel computing.
How to Use Parallel Processing in Global Optimization Toolbox
Direct a solver or hybrid function to use multiple processes.
Minimizing an Expensive Optimization Problem Using Parallel Computing Toolbox
Example showing the effectiveness of parallel computing in two solvers:fminconandga.
Improving Performance with Parallel Computing
Investigate factors for speeding optimizations.

Problem-Based Algorithms

Problem-Based Optimization Algorithms
Learn how the optimization functions and objects solve optimization problems.
Supported Operations for Optimization Variables and Expressions
空洞e the supported mathematical and indexing operations for optimization variables and expressions.