MOST EFFICIENT NLP TECHNIQUES IN OPTIMUM STRUCTURAL FRAME DESIGN

This paper identifies the two most efficient non-linear programming techniques for the solution of optimization problems of plane structural frames under multiple load systems. The problem is one of minimizing the mass or the frame subject to constraints on normal and shear stresses, the maximum tra...

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Vydané v:Engineering optimization Ročník 20; číslo 4; s. 261 - 272
Hlavný autor: KARIHALOO, B. L.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Taylor & Francis Group 01.02.1993
Gordon and Breach
Predmet:
augmented Lagrangian multiplier method
deflection and buckling constraints
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
minimum mass design
nonlinear programming
Physics
Plane structural frame
sequential convex programming
sequential linear programming
sequential quadratic programming
sequential unconstrained minimization
Solid mechanics
Static elasticity (thermoelasticity...)
stress
Structural and continuum mechanics
Lagrange multiplier
Truss structure
Sequential method
Non linear programming
Convex analysis
Optimization
Mathematical programming
ISSN:0305-215X, 1029-0273
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Shrnutí:This paper identifies the two most efficient non-linear programming techniques for the solution of optimization problems of plane structural frames under multiple load systems. The problem is one of minimizing the mass or the frame subject to constraints on normal and shear stresses, the maximum transverse deflection and buckling load. In all, five different NLP techniques are tried, and it is found that the sequential linear and sequential convex programming techniques are the most efficient for the solution of the class of NLP problems under consideration
ISSN:0305-215X
1029-0273
DOI:10.1080/03052159308941284