• Journal of Korean Society of Steel Construction
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• v.17 no.4 s.77
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• pp.385-394
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• 2005

In this paper, a discrete optimum design program was developed using the refined fuzzy-genetic algorithms based on the genetic algorithms and the fuzzy theory. The optimum design in this study can perform section and shape optimization simultaneously for planar and spatial steel structures. In this paper, the objective function is the weight of steel structures and the constraints are the design limits defined by the design and buckling strengths, displacements, and thicknesses of the member sections. The design variables are the dimensions and coordinates of the steel sections. Design examples are given to show the applicability of the discrete optimum design using the improved fuzzy-genetic algorithms in this study.

• Journal of Korean Association for Spatial Structures
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• v.5 no.4 s.18
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• pp.61-70
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• 2005

In paper the discrete optimum design program was developed using the continuous and discrete optimum algorithms based on the SUMT and genetic algorithms. In this paper, the objective function is the weight of structures and the constraints are limits state design limits method. The design variables are diameter and thick of steel pipe. Design examples are given to show the applicability of the optimum design using the continuous and discrete optimum algorithms based on the SUMT and genetic algorithms of this study.

• Journal of Korean Society of Steel Construction
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• v.13 no.5
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• pp.577-586
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• 2001

The objective of this study is the development of sizing and system shape discrete optime design algorithm which is based on the genetic algorithms (GAs). The algorithm can perform both size and shape optimum designs of space trusses. The developed algorithm was implemented in a computer program. The algorithm is known to be very efficient for the discrete optimization The genetic process selects the next design points based on the survivability of the current design points The evolutionary process evaluates the survivability of the design points selected from the genetic process in the genetic process of the simple genetic algorithms there are three basic operators : reproduction cross-over and mutation operators. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying the algorithm to optimum design examples.

• Journal of Korean Society of Steel Construction
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• v.19 no.2
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• pp.171-179
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• 2007

The greenhouse discrete optimum design program was developed using discrete optimum algorithm based on the genetic algorithm. The basic search method for the optimum design is the genetic algorithm, which is known to be very efficient for discrete optimization. In this paper, the objective function was the weight of the greenhouse structures and the constraints were the limits state design method. The design variables were galvanized steel pipes for plastic housing KSD 3760. Objective criteria were presented for the design of economic greenhouse structure and evaluation of its stability. The standardizations of greenhouse structure were used, as well as the normalization of greenhouse-related materials. Design examples were given to show the applicability of the optimum design using the discrete optimum algorithm based on the genetic algorithm of this study.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.2
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• pp.315-327
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• 2002

The main objective of this study is to develop an discrete optimization algorithm of plane steel frames with rigid using second-order-elastic-plastic hinge analysis which is considering panel zone. Conventional analyses of steel frame are usually tarried out without considering the effect of panel zone deformation on frame behavior The validity of this model is established by comparison without panel zone on joint models is analyzed numerically to demonstrate the importance of using realistic models in steel frame analysis. The objective function is taken as Weight of steel frames and the constraints we formulated based on AISC-LRFD(1994). The validity of the developed algorithm we demonstrate by comparing the result with those of SAP2000. The result of the study indicates that the optimal design algorithm considering of panel zone behavior more economic design than simple steel frame design methods.

• Journal of Korean Society of Steel Construction
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• v.13 no.6
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• pp.673-681
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• 2001

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithm. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the design points selected form the genetic process. The evolutionary process evaluates the survivability of the design points. The evolutionary process evaluates the survivability of the design points selected form the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithm was verified by applying the algorithm to optimum design examples.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.1-5
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• 2002

A common way to design a digital control system is to design an analog controller first and discretize it for digital implemention. In this paper, optimal digital controller design is studied within the framework of sampled -data control theory. In particular, multirate discretization of analog controller is considered using an Η$_2$optimality criterion. Solutions are obtained via multirate H2 optimization with a causality constraint due to the multirate structure. In design example, the comparison of the proposed methods is made with the conventional discretization methods, and demonstrate the superiority of the multirate design method.

• Computational Structural Engineering
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• v.15 no.1
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• pp.81-89
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• 2002

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.503-513
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• 2000

This study treats the criteria, considering the fuzziness occurred by optimization design. And we applied two weighting methods to show the relative importance of criteria. This study develops multi-objective optimization programs implementing plain stress analysis by FEM and discrete optimization design uniformaly. The developed program performs a sample design of 10-member steel truss. This study can carry over the multi-objective optimization based on total system fuzzy-genetic algorithms while performing the stress analysis and optimization design. Especially, when general optimization with unreliable constraints is cannot be solve this study can make optimization design closed to realistic with fuzzy theory.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.4
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• pp.97-107
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• 2006

This study is structural analysis and continuous, discrete optimum design of braced steel frame structures under earthquake loads considering soil condition. The program which is able to perform simultaneously structural analysis and continuous, discrete optimum design, it is applied steel frame structures using unbraced, Z-braced, and X-braced types and analyze the program about static loads and seismic loads. The purpose of this study is to present proper braced type for seismic effects by comparing and analyzing results of analytic method about various cases using specially Newmark-Hall design spectrum, ATC design spectrum and ATC equivalent static analysis and finding minimum weight and design variables which satisfy the ultimate strength requirements of AISC-ASD specifications, the serviceability requirements and allowable story drift requirements of ATC-3-06 and various constraints.