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# 문제 기반 최적화 설정

변수와 표현식을 사용하여 최적화 문제를 정식화하고 직렬 또는 병렬로 풀기

문제 기반 최적화에서는 최적화 변수를 만들어 이들 변수로 목적 함수와 제약 조건을 표현하거나 방정식을 나타내는 표현식을 만들고 `solve`를 사용하여 문제를 풉니다. 최적화 문제에 대해 수행할 문제 기반 절차를 보려면 Problem-Based Optimization Workflow 항목을 참조하십시오. 방정식 풀이에 대해서는 Problem-Based Workflow for Solving Equations 항목을 참조하십시오.

최적화 문제를 풀기 시작하기 전에 먼저 문제 기반 접근법과 솔버 기반 접근법 중 적절한 접근법을 선택해야 합니다. 자세한 내용은 먼저 문제 기반 접근법 또는 솔버 기반 접근법 중 선택하기 항목을 참조하십시오.

참고: 다항식이나 유리식, 기본 함수(예: `exp`)로 구성되지 않은 비선형 함수가 있는 경우에는 `fcn2optimexpr`을 사용하여 해당 함수를 최적화 표현식으로 변환하십시오. Convert Nonlinear Function to Optimization Expression 항목과 Supported Operations on Optimization Variables and Expressions 항목을 참조하십시오.

기본적인 비선형 최적화 예제를 보려면 제약 조건이 있는 비선형 문제 풀기, 문제 기반 항목을 참조하십시오. 기본적인 혼합 정수 선형 계획법 예제를 보려면 혼합 정수 선형 계획법 기본 사항: 문제 기반 항목을 참조하십시오. 기본 방정식 풀이 예제를 보려면 Solve Nonlinear System of Equations, Problem-Based 항목을 참조하십시오.

## 함수

모두 확장

 `eqnproblem` Create equation problem `optimproblem` 최적화 문제 만들기 `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
 `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
 `evaluate` Evaluate optimization expression `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` 최적화 문제 또는 방정식 문제 풀기 `varindex` Map problem variables to solver-based variable index `write` Save optimization object description

## 객체

 `EquationProblem` System of nonlinear equations `OptimizationConstraint` Optimization constraints `OptimizationEquality` Equalities and equality constraints `OptimizationExpression` Arithmetic or functional expression in terms of optimization variables `OptimizationInequality` Inequality constraints `OptimizationProblem` Optimization problem `OptimizationVariable` Variable for optimization

## 도움말 항목

### 문제 기반 절차

Problem-Based Optimization Workflow

Problem-based steps for solving optimization problems.

Problem-Based Workflow for Solving Equations

Problem-based steps for solving equations.

Optimization Expressions

Expressions define both objective and constraints.

Pass Extra Parameters in Problem-Based Approach

Pass extra parameters, data, or fixed variables in the problem-based approach.

Write Objective Function for Problem-Based Least Squares

Syntax rules for problem-based least squares.

Named Index for Optimization Variables

How to create and work with named indices for variables.

Review or Modify Optimization Problems

Shows how to review or modify problem elements such as variables and constraints.

Examine Optimization Solution

How to evaluate the solution and its quality.

### 옵션 설정하기

옵션 설정하기

최적화 옵션 설정

Output Function for Problem-Based Optimization

Shows how to use an output function in the problem-based approach to record iteration history and to make a custom plot.

### 문제 기반 최적화를 위한 팁

Create Efficient Optimization Problems

Tips for obtaining a faster or more accurate solution when there are integer constraints, and for avoiding loops in problem creation.

Separate Optimization Model from Data

To create reusable, scalable problems, separate the model from the data.

Variables with Duplicate Names Disallowed

Solution to the problem of two optimization variables with the same name.

Create Initial Point for Optimization with Named Index Variables

This example shows how to create initial points for `solve` when you have 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 your objective and nonlinear constraint functions share common computations in the problem-based approach.

Effect of Automatic Differentiation in Problem-Based Optimization

Automatic differentiation lowers the number of function evaluations for solving a problem.

### 병렬 연산

What Is Parallel Computing in Optimization Toolbox?

Use multiple processors for optimization.

Using Parallel Computing in Optimization Toolbox

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.

### 문제 기반 알고리즘

Problem-Based Optimization Algorithms

How the optimization functions and objects solve optimization problems.

Automatic Differentiation Background

Learn how automatic differentiation works.

Supported Operations on Optimization Variables and Expressions

Lists all available mathematical and indexing operations on optimization variables and expressions.