다중 목적 함수 최적화
제약 조건이 있거나 제약 조건이 없는 경우에서, 유전 알고리즘 또는 패턴 탐색 알고리즘을 통한 파레토 집합
동시에 최적화하려는 목적 함수가 여러 개 있는 경우 이들 솔버는 경쟁하는 목적 함수들 사이에서 최적의 절충점을 찾습니다.
함수
객체
OptimizationValues | 최적화 문제의 값 (R2022a 이후) |
라이브 편집기 작업
최적화 | 라이브 편집기에서 방정식을 최적화하거나 풉니다. (R2020b 이후) |
도움말 항목
문제 기반 다중 목적 함수 최적화
- Steps for Problem-Based Multiobjective Optimization
How to set up and evaluate results of multiobjective optimization problems. - Pareto Front for Multiobjective Optimization, Problem-Based
This example shows how to create and plot the solution to a multiobjective optimization problem. - Plan Nuclear Fuel Disposal Using Multiobjective Optimization
Plan the disposal of spent nuclear fuel while minimizing both cost and risks. This example has both continuous and binary variables.
솔버 기반 다중 목적 함수 최적화
- Pareto Front for Two Objectives
Shows an example of how to create a Pareto front and visualize it. - Design Optimization of a Welded Beam
Shows tradeoffs between cost and strength of a welded beam. - Compare paretosearch and gamultiobj
Solve the same problem usingparetosearch
andgamultiobj
to see the characteristics of each solver. - Performing a Multiobjective Optimization Using the Genetic Algorithm
Solve a simple multiobjective problem using plot functions and vectorization. - Effects of Multiobjective Genetic Algorithm Options
Shows the effects of some options on thegamultiobj
solution process. - When to Use a Hybrid Function
Describes cases where hybrid functions are likely to provide greater accuracy or speed. - Plot 3-D Pareto Front
Plot a Pareto set in three dimensions.
다중 목적 함수 배경 정보
- What Is Multiobjective Optimization?
Describes Pareto-optimal sets. - gamultiobj Algorithm
How thegamultiobj
algorithm works. - paretosearch Algorithm
Describes theparetosearch
algorithm. - gamultiobj Options and Syntax: Differences from ga
Describes differences between the options forga
andgamultiobj
. - Genetic Algorithm Options
Explore the options for the genetic algorithm. - Pattern Search Options
Explore the options for pattern search.