In order to study the comparison of material design, structure design and integrated design about the porous material, a concurrent topology optimization design model associating materials and structures with periodic...
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ISBN:
(纸本)9783037851920
In order to study the comparison of material design, structure design and integrated design about the porous material, a concurrent topology optimization design model associating materials and structures with periodical microstructures is presented. The sensitivity formulae of hierarchy optimization are given based on the integrated design model and related numerical experiments were carried out. The applicability of hierarchy optimization is discussed and their advantage and disadvantage are analyzed through numerical examples which provide some useful opinions about the porous material design.
A problem of a hierarchy structure optimization is *** structures arewidely used in the Analytic hierarchy Process,conjoint analysis,and various other methods of multiplecriteria decision *** problem consists in findi...
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A problem of a hierarchy structure optimization is *** structures arewidely used in the Analytic hierarchy Process,conjoint analysis,and various other methods of multiplecriteria decision *** problem consists in finding a structure that needs a minimum number ofpair comparisons for a given total number of the *** an optimal hierarchy,the minimumefforts are needed for eliciting data and synthesizing the local preferences across the hierarchy to getthe global priorities or *** estimation techniques are developed and numerical *** and numerical results suggest optimal ways of priority evaluations for practicalmanagerial decisions in a complex environment.
A method of description and optimization of the structure of hierarchical processing systems is presented. The set of feasible structures for such class of systems is defined. The representation of this set is constru...
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ISBN:
(纸本)9789955282839
A method of description and optimization of the structure of hierarchical processing systems is presented. The set of feasible structures for such class of systems is defined. The representation of this set is constructed in terms of the graph theory. For the reduced statement two types of variable parameters are defined: for the level size and for the relations of adjacent levels. The choice of variable parameters guarantees the discrete-convexity of objective function. A class of iteration methods for solving the discrete-convex programming problem is derived. The method based on the extension of discrete-convex function to the convex function and on extension of discrete-convex programming problem to the convex programming problem. On each step of the iteration the calculation of the value of objective function is required only on some vertices of unit cube. The considered approach is illustrated by an academic example of modelling and optimization of the structure of multi-level processing system.
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