Optimization of Distributed Parameter Structures — Volume I 1981
DOI: 10.1007/978-94-009-8603-9_30
|View full text |Cite
|
Sign up to set email alerts
|

The Integrated Approach of FEM-SLP for Solving Problems of Optimal Design

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
7
0

Year Published

1987
1987
2013
2013

Publication Types

Select...
6
1
1

Relationship

0
8

Authors

Journals

citations
Cited by 17 publications
(7 citation statements)
references
References 12 publications
0
7
0
Order By: Relevance
“…This led to the Sequential Linear Programming (SLP) method and the wide use of the linear Taylor series approximations. Applications can be found in the paper by Zienkiewicz and Campbell (1973) who optimize the shape of dams and in the paper by Pedersen (1981) who finds the optimum design of space trusses, for example. Another reason for the popularity of local approximations is that, as discussed later, some global approxhnations become very expensive computationally when the dimensionality of the design space becomes large.…”
Section: I Local Function Approximationsmentioning
confidence: 97%
“…This led to the Sequential Linear Programming (SLP) method and the wide use of the linear Taylor series approximations. Applications can be found in the paper by Zienkiewicz and Campbell (1973) who optimize the shape of dams and in the paper by Pedersen (1981) who finds the optimum design of space trusses, for example. Another reason for the popularity of local approximations is that, as discussed later, some global approxhnations become very expensive computationally when the dimensionality of the design space becomes large.…”
Section: I Local Function Approximationsmentioning
confidence: 97%
“…The above minimization problem was solved by nonlinear mathematical programming techniques, namely sequential linear programming (SLP) with move-limits (Pedersen 1981), sequential quadratic programming (SQP) (Powell 1977) and sequential convex programming (SCP) (Fleury and Braibant 1986), which are available in the general purpose structural optimization package ADS (Vanderplaats 1987). It was found that among the three strategies, SLP and SCP terminated with fewer functional evaluations but more gradient calculations than SQP.…”
Section: Coy Q-cyy D=mentioning
confidence: 99%
“…The above minimization problem was solved by nonlinear mathematical pro gramming techniques, namely sequential linear programming (SLP) with movelimits (Pedersen 1981), sequential quadratic programming (SQP) (Powell 1977) and sequential convex programming (SCP) (Fleury &;Braibant 1986) which are available in the general purpose structural optimization package ADS (Vanderplaats 1987). The number of functional and gradient evaluations for the above problem and an alternative formulation to be considered below, are given in ta ble 2.…”
Section: Optimization Problem and Solutionmentioning
confidence: 99%