# Problem-Based Global Optimization Setup

`solve`

Global Optimization Toolbox has two approaches for optimization: problem-based and
solver-based. See Decide 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 using `solve`

. For details, see Problem-Based Optimization Workflow.

**Note:** If you have a nonlinear function
that is not composed of polynomials, rational expressions, and elementary
functions such as `exp`

, then convert the function to an
optimization expression by using `fcn2optimexpr`

. See Convert Nonlinear Function to Optimization Expression and
Supported Operations for Optimization Variables and Expressions.

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

## Functions

## 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 (Since R2022a) |

`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**

Explore considerations for problem-based and solver-based optimization with Global Optimization Toolbox solvers.**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 for Global Optimization Toolbox solvers in the problem-based approach.**Integer Constraints in Nonlinear Problem-Based Optimization**

Learn how the problem-based optimization functions`prob2struct`

and`solve`

handle integer constraints.

### Set Global Optimization Options

**Set Problem-Based Optimization Options for Global Optimization Toolbox Solvers**

How to set and change optimization options in the problem-based approach for Global Optimization Toolbox.**Set Options in Problem-Based Approach Using varindex**

To set options in some contexts, map problem-based variables to solver-based using`varindex`

.**Pattern Search Options**

Explore the options for pattern search.**Genetic Algorithm Options**

Explore the options for the genetic algorithm.**Particle Swarm Options**

Explore the options for particle swarm.**Surrogate Optimization Options**

Explore the options for surrogate optimization, including algorithm control, stopping criteria, command-line display, and output and plot functions.**Simulated Annealing Options**

Explore 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 for`solve`

when the problem has named index variables by using the`findindex`

function.**Expression Contains Inf or NaN**

Optimization expressions containing`Inf`

or`NaN`

cannot 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 by`prob2struct`

.**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:`fmincon`

and`ga`

.**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**

Explore the supported mathematical and indexing operations for optimization variables and expressions.