Optimum Design of Trusses From Available Sections—use of Sequential Linear Programming With Branch and Bound Algorithm

John, Keerthana; Ramakrishna, C. V.; Sharma, Kalpana

doi:10.1080/03052158808940951

Cited by 19 publications

(8 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…7, March 39 variables have been solved traditionally by implicit enumeration procedure, branch and bound algorithm, etc. An approximate method using a heuristic approach had been suggested by the authors in an earlier publication 8 . When tight constraints are present on natural frequencies, it is not clear how a heuristic discrete choice of the members can be made.…”

Section: Optimization Algorithmmentioning

confidence: 99%

“…In actual practice, the available sections are finite in number and a suitable procedure to select members from this set should be developed with the aim of weight minimization. In an earlier work, the authors brought out the usefulness of a discrete programming algorithm and certain approximate optimization techniques in the context of structural optimization of trusses with stress and displacement constraints 8 . In this paper, this method has been extended to problems with frequency constraints.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Discrete optimal design of trusses with stress and frequency constraints

John

Ramakrishnan

1990

Engineering Computations

View full text Add to dashboard Cite

The problem of structural optimization of trusses subject to stress and frequency constraints is considered from a practical viewpoint. Assuming that the choice of members has to be from a discrete set of available sections, the solution is attempted using a mathematical programming approach and an approximate two‐step procedure involving a continuous variable optimization followed by a discrete programming algorithm. The latter approach is highly promising for problems involving stress and frequency constraints. Detailed results are presented using several benchmark problems.

show abstract

Section: Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Discrete optimal design of trusses with stress and frequency constraints

John

Ramakrishnan

1990

Engineering Computations

View full text Add to dashboard Cite

show abstract

“…As demonstrated by John et al (1988), an approximate xr curve, based on regression analysis, may be used in the continuous phases of the algorithm. John et al (1988) performed direct interpolation between z and r, using secondand third-order polynomials, as well as a power curve.…”

Section: Interpolating Curvesmentioning

confidence: 99%

“…John et al (1988) performed direct interpolation between z and r, using secondand third-order polynomials, as well as a power curve. The present study employs the transformation r = v/~ to obtain a relationship between r and z in the ~ -z domain (Figs.…”

Section: Interpolating Curvesmentioning

confidence: 99%

See 1 more Smart Citation

Optimal discrete sizing of truss structures subject to buckling constraints

Groenwold

Stander

1997

Structural Optimization

View full text Add to dashboard Cite

The selective dynamic rounding (SDR) algorithm previously developed by the authors, and based on a dual step rounding approach, is used for the optimal sizing design of truss structures subject to linear buckling constraints. The algorithm begins with a continuous optimum followed by a progressive freezing of individual variables while solving the remaining continuous problems. The allowable member stresses are predicted by the linear regression of the tabular section properties, while the exact allowable compressive stresses are back-substituted for those variables fixed on discrete values in each intermediate mixed-discrete nonlinear problem. It is shown that a continuous design based on the regression analysis of section effectiveness vs. area is effective as a starting point for the dual step discrete optimization phase. A range of examples is used to illustrate that with "conservative" regression, discrete designs can be achieved which are significantly lighter than those in which the variables have been rounded up.

show abstract

A regional genetic algorithm for the discrete optimal design of truss structures

Groenwold

Stander

Snyman

1999

Int. J. Numer. Meth. Engng.

View full text Add to dashboard Cite

A regional genetic algorithm (R‐GA) is used for the discrete optimal design of truss structures. The chromosomes are selected from a sub‐region centred on the continuous optimum. This approach replaces genetic rebirth as previously proposed by other authors, thereby significantly reducing computational costs. As a pure discrete method, the R‐GA method does not require heuristic arguments or approximations. This makes the algorithm highly effective when buckling and slenderness constraints with scatter in the data are introduced. A large set of numerical test examples is used to illustrate the capabilities of the method. The algorithm is shown to be effective and robust, making it suitable for the optimal design of very large truss structures. Copyright © 1999 John Wiley & Sons, Ltd.

show abstract

Optimum Design of Trusses From Available Sections—use of Sequential Linear Programming With Branch and Bound Algorithm

Cited by 19 publications

References 8 publications

Discrete optimal design of trusses with stress and frequency constraints

Discrete optimal design of trusses with stress and frequency constraints

Optimal discrete sizing of truss structures subject to buckling constraints

A regional genetic algorithm for the discrete optimal design of truss structures

Contact Info

Product

Resources

About