M
Mehmet Polat Saka
Researcher at University of Bahrain
Publications - 85
Citations - 3388
Mehmet Polat Saka is an academic researcher from University of Bahrain. The author has contributed to research in topics: Harmony search & Metaheuristic. The author has an hindex of 32, co-authored 84 publications receiving 3051 citations. Previous affiliations of Mehmet Polat Saka include Karadeniz Technical University & Middle East Technical University.
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Optimum design of steel frames with stability constraints
TL;DR: In this paper, the authors presented an algorithm for the optimum design of street frames that implements the displacement and combined stress limitations according to AISC, and the recursive relationship for design variables in the case of dominant displacement constraints is obtained by the optimality criteria approach.
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Ant colony optimization of irregular steel frames including elemental warping effect
TL;DR: The optimum design problem of steel space frames is formulated according to the provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction) in which the effect of warping is also taken into account.
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Genetic algorithm based optimum bracing design of non-swaying tall plane frames
E.S. Kameshki,Mehmet Polat Saka +1 more
TL;DR: In this paper, a genetic algorithm based optimum design method for multi-storey non-swaying steel frames with different types of bracing is presented, which obtains a frame and bracing system with the least weight by selecting appropriate sections for beams, columns, and BRacing members from the standard set of steel sections.
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Optimum geometry design of nonlinear braced domes using genetic algorithm
E. S. Kameshki,Mehmet Polat Saka +1 more
TL;DR: In this paper, an algorithm is presented for the optimum geometry design of nonlinear braced domes, where the height of crown is taken as design variable in addition to the cross-sectional properties of members.
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Guided stochastic search technique for discrete sizing optimization of steel trusses: A design-driven heuristic approach
TL;DR: In this article, a design-driven heuristic approach named guided stochastic search (GSS) technique for discrete sizing optimization of steel trusses is presented, which works on the basis of guiding the optimization process using the well-known principle of virtual work.