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.
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 |
Problem-Based Optimization Workflow
Problem-based steps for solving optimization problems.
Problem-Based Workflow for Solving Equations
Problem-based steps for solving equations.
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.
How to evaluate the solution and its quality.
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.
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.
What Is Parallel Computing in Optimization Toolbox?
Use multiple processors for optimization.
Using Parallel Computing in Optimization Toolbox
Perform gradient estimation in parallel.
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 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.