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.
문제 기반 접근법에서는 문제 변수를 생성한 후 기호화된 변수로 목적 함수와 제약 조건을 나타냅니다. 문제 기반으로 수행할 절차를 보려면 Problem-Based Optimization Workflow 항목을 참조하십시오. 결과로 생성된 문제를 풀려면 solve
를 사용하십시오.
솔버 기반으로 수행할 절차를 보려면 솔버 기반 최적화 문제 설정 항목을 참조하십시오. 목적 함수와 제약 조건을 정의하고 적합한 솔버를 선택하는 등의 작업이 설명되어 있습니다. 결과로 생성된 문제를 풀려면 quadprog
또는 coneprog
를 사용하십시오.
최적화 | Optimize or solve equations in the Live Editor |
SecondOrderConeConstraint | Second-order cone constraint object |
Quadratic Programming with Bound Constraints: Problem-Based
Shows how to solve a problem-based quadratic programming problem with bound constraints using different algorithms.
Large Sparse Quadratic Program, Problem-Based
Shows how to solve a large sparse quadratic program using the problem-based approach.
Bound-Constrained Quadratic Programming, Problem-Based
Example showing large-scale problem-based quadratic programming.
기본 포트폴리오 모델에서 문제 기반 2차 계획법을 보여주는 예제입니다.
Quadratic Minimization with Bound Constraints
Example of quadratic programming with bound constraints and various options.
Quadratic Programming with Many Linear Constraints
This example shows the benefit of the active-set algorithm on problems with many linear constraints.
Quadratic Minimization with Dense, Structured Hessian
Example showing how to save memory in a structured quadratic program.
Large Sparse Quadratic Program with Interior Point Algorithm
Example showing how to save memory in a quadratic program by using a sparse quadratic matrix.
Bound-Constrained Quadratic Programming, Solver-Based
Example showing solver-based large-scale quadratic programming.
Quadratic Programming for Portfolio Optimization Problems, Solver-Based
Example showing solver-based quadratic programming on a basic portfolio model.
Minimize Energy of Piecewise Linear Mass-Spring System Using Cone Programming
Solve a mechanical mass-spring problem using cone programming.
Convert Quadratic Constraints to Second-Order Cone Constraints
Convert quadratic constraints into coneprog
form.
Convert Quadratic Programming Problem to Second-Order Cone Program
Convert a quadratic programming problem to a second-order cone problem.
Code Generation for quadprog Background
Prerequisites to generate C code for quadratic optimization.
Learn the basics of code generation for the quadprog
optimization solver.
Optimization Code Generation for Real-Time Applications
Explore techniques for handling real-time requirements in generated code.
Problem-Based Optimization Algorithms
How the optimization functions and objects solve optimization problems.
Supported Operations on Optimization Variables and Expressions
Lists all available mathematical and indexing operations on optimization variables and expressions.
선형 제약 조건과 범위 제약 조건만 적용하여 n차원에서 2차 목적 함수를 최소화합니다.
Second-Order Cone Programming Algorithm
Description of the underlying algorithm.
최적화 옵션을 살펴봅니다.