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Titlebook: Discrete Structural Optimization; W. Gutkowski Book 1997 Springer-Verlag Wien 1997 design.machines.optimization.structural optimization

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https://doi.org/10.1007/978-3-7091-2754-4design; machines; optimization; structural optimization
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978-3-211-82901-1Springer-Verlag Wien 1997
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Discrete Structural Optimization978-3-7091-2754-4Series ISSN 0254-1971 Series E-ISSN 2309-3706
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Discrete Structural Optimization: Design Problems and Exact Solution Methods,t known designs of this kind are those in which the variables are selected from given finite sets of values. In most cases these sets are lists of prefabricated structural and machine elements available on the market. Also some other more complex problems of DSO are discussed. There are designs in w
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Stochastic Search in Discrete Structural Optimization Simulated Annealing, Genetic Algorithms and Nitional continuous variable problems. In some applications, the number of design variables may be quite large. Additionally, the design space in such problems may be nonconvex, and in some situations, even disjointed. The use of conventional mathematical programming methods in such problems is fraug
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Heuristic Methods in Discrete Structural Optimization,which are available in discrete sizes. As a vehicle for describing the methods the optimum design of trusses using rolled steel sections is used. The combinatorial nature of the problem is first briefly described and the necessity for heuristic methods for finding non-rigorous but very close discret
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Backtrack Method with Applications to Dso,rete series of values are given for variables, the discrete optima can be determined by a complementary discretization which is also explained. Optimum design problems of stiffened and cellular plates, tubular trusses, welded box beams and welded steel silos are treated. In these applications the di
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Dual Methods in Discrete Structural Optimization,ll elaborated methods of continuous optimum structural design is not possible..In this chapter the dual approach in a discrete structural optimization problems is presented The constraints of the problem are scaled by means of Lagrangean multipliers, added to the cost function and relaxing from the
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