• Journal of Korean Association for Spatial Structures
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• v.2 no.3 s.5
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. 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 algorithms. 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 current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.43-52
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• 2004

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algerian 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 algorithms. 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 current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• Journal of Korean Association for Spatial Structures
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• v.1 no.1 s.1
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• pp.125-134
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• 2001

The objective of this study is the development of size discrete optimum design algorithm which is based on the GAs(genetic algorithms). The algorithm can perform size discrete optimum designs of space trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses and the constraints are limite state design codes(1998) and displacements. The basic search method for the optimum design is the GAs. The algorithm is known to be very efficient for the discrete optimization. This study solves the problem by introducing the GAs. The GAs consists of genetic process and evolutionary process. 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 GAs, 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 GAs to optimum design examples.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.16-25
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• 1999

In recent years, grinding techniques for precision machining of brittle materials used in die, model and optical parts have been improved by using superfine abrasive wheel and precision grinding machine. The completion of optimum dressing of superfine abrasive wheel makes possible the effective precision grinding of die steel(STD-11). In this study, a new system and the grinding mechanism of optimum in-process electrolytic dressing were proposed. This method can carry out optimum in-process electrolytic dressing of superfine abrasive wheel. Therefore, the optimum in-process electrolytic dressing is a good method to obtain the efficiency and mirror-like grinding of STD-11.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.111-116
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• 2005

This paper considers the problem of optimally choosing the sub-process means of a mixture production process where two important ingredients are mixed. The quantity of each ingredient is controlled through each corresponding sub-process. The values of the sub-process mean directly affect the defective rate, production, scrap and reprocessing costs for the mixture production process. After inspecting every incoming item, each conforming item is sold in a regular market for a fixed price and any nonconforming item is scraped. A model is constructed on the basis of the selling price, production, inspection, and scrap and reprocessing costs. The goal is to determine the optimum sub-process mean values based on maximizing expected profit function relating selling price and cost components. A method of finding the optimum sub-process means is presented when the quantities of the two ingredients are assumed to be normally distributed with known variances. A numerical example is given and numerical studies are performed.

• Architectural research
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• v.4 no.1
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• pp.33-38
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• 2002

The objective of this study is the development of discrete optimum design algorithms which is based on the genetic algorithms. The developed algorithms was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses structures and the constraints are stresses and displacements. This study solves the problem by introducing the genetic algorithms. The genetic algorithms consists of genetic process and evolutionary process. 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. The efficiency and validity of the developed discrete optimum design algorithms was verified by applying the algorithms to optimum design examples.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.25-30
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• 1997

In recent years, grinding techniques for precision machining of astainless steel used in shaft, screw parts and clear value have been improved by using superabrasive wheel and precision grinding machine. The completion of optimum dressing of superabrasive wheel makes possible the effective percision grinding of stainless steel. However, the present dressing system cannot have control of optimum dressing of the superabrabive wheel. In this study, a new system and the grinding mechanism of optimum in-process electrolytic dressing were proposed. This system can carry out optimum in-process dressing of superabrasive wheel. Therefore, the optimum in-process electrolytic dressing is a good method to obtain the efficiency and mirror-like grinding of stainless steel(SUS304).

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.680-687
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• 1995

In recent years, grinding techniques for precision machining of brittle materials used in electric, optical and magnetic parts have been improved by using superabrasive wheel and precision grinding machine. The completion of optimum dressing of superabrasive wheel makes possible the effective precision grinding of brittle materials. But the present dressing system cannot have control of optimum dressing of the superabrasive wheel. This study has proposed a new optimum in-process electrolytic dressing system. This system can carry out optimum in-process dressing of superabrasive wheel, and give very effective control according to gap increase.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.5
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• pp.29-37
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• 1998

In recent years, grinding techniques for precision machining of stainless steel used in shaft, screw parts and clear value have been improved by using the superabrasive wheel and precision grinding machine. The completion of optimum dressing of superabrasive wheel makes possible the effective precision grinding of stainless steel. However, the present dressing system cannot have control of optimum dressing of the superabrasive wheel. In this study, a new system and the grinding mechanism of optimum in-process dressing of superabrasive wheel. Therefore, the optimum in-process electrolytic dressing is a good method to obtain the efficiency and mirror-like grinding of stainless steel (STS304)