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Published byAdam Adenauer Modified 6년 전
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5. 비제약 최적설계의 수치해법 (Numerical Methods for Unconstrained Optimum Design)
NLP (Nonlinear Programming) 최적설계의 수치해법 초기설계 추정 최적성 조건이 만족할 때 까지 반복
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비제약 최적화문제의 분류
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Unconstrained Optimization
일차원 최소화 (One Dim. Minimization) 최속강하법 (Steepest Descent Method) 공액경사도법 (Conjugate Gradient M.) 뉴톤의 방법 (Newton’s Method) 유사뉴톤방법 (Quasi-Newton Method) 공학적 응용 (Engineering Applications) 최적설계 변환법 (Transformation Methods)
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5.2 수치알고리즘의 일반개념 Analytical approach: Numerical methods:
Optimality conditions Candidate local minimum design Numerical methods: Initial design Iterations until optimality conditions satisfied
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5.2.1 A General Algorithms Vector form 현재 설계에서의 미소 변화 Component form
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Change in design 현재 설계에서의 미소 변화 Step size Search direction
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Change in design
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5.2.2 Descent Step Idea (강하, 감소)
Desirable direction of design change (바람직한 설계 변화의 방향)
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Searching Direction (탐색방향)
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Descent direction (강하방향)
Descent condition (강하조건)
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5.2.3 Convergence of Algorithms
The property of convergence to a local optimum point irrespective of the starting point 5.2.4 Rate of Convergence Faster algorithms use 2nd order information of the function Newton’s Method, Quasi-Newton method
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5.3 One-dimensional Minimization
Step size Search direction
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5.3 One-dimensional minimization
5.3.1 Problem Definition 5.3.2 Equal Interval Search (등간격 탐색) 5.3.3 Golden Section Search (황금분할 탐색) 5.3.4 Polynomial Interpolation (다항식 보간법)
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Problem Definition 설계변화 탐색 방향을 찾았다면 known unknown
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Change in design
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일변수 함수로의 환원 기하학적 의미 목적함수의 강하조건
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목적함수의 강하조건 음수
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Step size 계산법 Step size - 이동거리 이동거리 계산법 해석적 방법 (Analytical Method)
수치적 방법 (Numerical Method)
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Analytical Method for step size
를 최소화하기 위한 필요조건 충분조건
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Numerical method for step size
Unimodal function if =
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Equal Interval Search (등간격 탐색)
초기추정
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Equal Interval Search (등간격 탐색)
불확정 구간의 감소
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5.3 Golden Section Search (황금분할탐색)
Initial bracketing (최소치의 초기 추정) Fibonacci sequence – Golden ratio Reduction of interval of uncertainty (불확정 구간의 축소)
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Fibonacci Sequence 피보나치 수열 황금비
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황금분할법 - 초기추정
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황금분할법 - 초기구간 추정
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불확정구간 축소
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5.4 Steepest Descent Method (최속강하법)
탐색방향을 구하는 방법 First order method: Steepest Descent Method Second order method: Newton’s Method Desirable direction of design change (바람직한 설계 변화의 방향)
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Steepest Descent Algorithm
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5.5 Conjugate Gradient Method (공액경사도방법)
By Fletcher & Reeves (1964) Very simple and effective modification of the Steepest Descent Method
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5.5 Conjugate Gradient Method (공액경사도방법)
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5.6 Newton’s Method 2nd order information 사용
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5.6 Newton’s Method Modified Newton’s Method
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Example 5.16
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Marquardt Modification
DFP (Davidon,Fletcher,Powell) Approximate Inverse of Hessian BFGS (Broyden,Fletcher,Goldfarb,Shannon) Update Hessian at every iteration
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