Browsing by Author "Hasancebi, O."

Now showing 1 - 2 of 2

Citation - WoS: 44
Citation - Scopus: 50
Computationally Efficient Discrete Sizing of Steel Frames Via Guided Stochastic Search Heuristic
(Pergamon-elsevier Science Ltd, 2015) Azad, S. Kazemzadeh; Hasancebi, O.
Recently a design-driven heuristic approach named guided stochastic search (GSS) technique has been developed by the authors as a computationally efficient method for discrete sizing optimization of steel trusses. In this study, an extension and reformulation of the GSS technique are proposed for its application to problems from discrete sizing optimization of steel frames. In the GSS, the well-known principle of virtual work as well as the information attained in the structural analysis and design stages are used together to guide the optimization process. A design wise strategy is employed in the technique where resizing of members is performed with respect to their role in satisfying strength and displacement constraints. The performance of the GSS is investigated through optimum design of four steel frame structures according to AISC-LRFD specifications. The numerical results obtained demonstrate that the GSS can be employed as a computationally efficient design optimization tool for practical sizing optimization of steel frames. (C) 2015 Elsevier Ltd. All rights reserved.
Citation - WoS: 33
Citation - Scopus: 37
Discrete Sizing Optimization of Steel Trusses Under Multiple Displacement Constraints and Load Cases Using Guided Stochastic Search Technique
(Springer, 2015) Azad, S. Kazemzadeh; Hasancebi, O.
The guided stochastic search (GSS) is a computationally efficient design optimization technique, which is originally developed for discrete sizing optimization problems of steel trusses with a single displacement constraint under a single load case. The present study aims to investigate the GSS in a more general class of truss sizing optimization problems subject to multiple displacement constraints and load cases. To this end, enhancements of the GSS are proposed in the form of two alternative approaches that enable the technique to deal with multiple displacement/load cases. The first approach implements a methodology in which the most critical displacement direction is considered only when guiding the search process. The second approach, however, takes into account the cumulative effect of all the critical displacement directions in the course of optimization. Advantage of the integrated force method of structural analysis is also utilized for further reduction of the computational effort in these approaches. The proposed enhancements of GSS are investigated and compared with some selected techniques of design optimization through six truss structures that are sized for minimum weight. The numerical results reveal that both enhancements generally provide promising solutions with an insignificant computational effort.