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发表于 2008-3-4 08:41:48
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来自 加拿大
For your reference:
There are two popular multidisciplinary computer-aided-optimization (CAO) software that can be used for FE-model optimization: LMS-Optimus and iSIGHT.
1. OPTIMUS
Optimus has the following optimization algorithms:
 Gradient-based nonlinear programming techniques (local methods)
o Sequential quadratic programming
o Conjugate gradient methods
 Genetic algorithms (global methods)
o Self-adaptive evolutionary algorithm
o Differential evolutionary algorithm
o Simulated annealing
 Response surface-based methods
o Linear, quadratic, tri
o O-RSM model
o User-defined surrogates
 Random search
 Feasible direction method
 Design-of-experiment (DOE)
o Quarter Fractional Factorial
o Latin hypercube
o Taguchi, Plackett and Burman
o User-difened DOE
 Multi-objective optimization
 Numerical sensitivity analysis
 Integer programming
 User-defined optimization algorithms
 Probabilistic optimization using Monte Carlo simulation
o Design variables can be defined as Gaussian, Exponential, Rayleigh distributions
o ser-defined probabilistic distribution
OPTIMUS has a GUI, and a script language for users to write scripts controlling the optimization process. Users can also write JAVA codes to control the optimization.
OPTIMUS is said can be connected to any FEA software and programs, including user-written codes in MATLAB and C.
2. ISIGHT
The optimization techniques in iSIGHT can be divided into three main categories:
 Numerical Optimization Techniques
 Exploratory Techniques
 Expert System Techniques
Numerical optimization techniques generally assume the parameter space is unimodal, convex, and continuous. The techniques including in iSIGHT are:
 ADS-based Techniques
 Exterior Penalty
 Modified Method of Feasible Directions
 Sequential Linear Programming
 Generalized Reduced Gradient - LSGRG2
 Hooke-Jeeves Direct Search Method
 Method of Feasible Directions - CONMIN
 Mixed Integer Optimization - MOST
 Sequential Quadratic Programming - DONLP
 Sequential Quadratic Programming - NLPQL
 Successive Approximation Method
The numerical optimization techniques can be further divided into the following two categories:
 direct methods
 penalty methods
 Direct Methods
o Generalized Reduced Gradient - LSGRG2
o Method of Feasible Directions - CONMIN
o Mixed Integer Optimization - MOST
o Modified Method of Feasible Directions - ADS
o Sequential Linear Programming - ADS
o Sequential Quadratic Programming - DONLP
o Sequential Quadratic Programming - NLPQL
o Successive Approximation Method
 Penalty methods
o Exterior penalty
o Hooke-Jeeves Direct Search
Exploratory techniques avoid focusing only on a local region. They generally evaluate designs throughout the parameter space in search of the global optimum. The techniques included in iSIGHT are:
 Adaptive Simulated Annealing
 Multi-Island Genetic Algorithm
Expert system techniques follow user defined directions on what to change, how to change it, and when to change it. The technique including in iSIGHT is
 Directed Heuristic Search (DHS) .
iSIGHT also has a GUI, and can be connected to most of the FEA programs.
3. COMSOL
Comsol is actually implemented in Matlab as a toolbox. Therefore, Comsol is able to output exactly what it having Matlab do as a series of commands in an m file (a Matlab script). Each major action (usually involving hitting ok and a statement at the bottom of the main window) performed in Comsol maps to a statement written in the m file, in the order they are performed. For example, if you hit the "Refine Mesh" button, it corresponds to a line in the m file.
The advantage of COMSOL is that it can naturally be connected into MATLAB, and all the MATLAB optimization resources can be used to do model-update with COMSOL. |
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