• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.46-51
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• 2014

The most important process of engineering system optimal design is to identify the relationship between the design variables and system response. In case of the system optimization, Response Surface Method (RSM) is widely used. The optimization process of RSM generates the design space using the typical alternative candidates and finds the optimal design point in the generated design space. By changing the optimal point depending on the configuration of the design space, it is important to generate the design space. Therefor in this study, the design space is generated by using the relationship between design variables and system response based on Neuro-Response Surface Method (NRSM). And I try to construct the framework for optimal shape design based on NRSM that the optimum shape can be predicted using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) within the generated design space. In order to verify the usefulness of the constructed framework, we applied the nonlinear mathematical function problem. In this study, we can solve the constraints of time in the optimization process for the engineering problem and effective to determine the optimal design was possible. by using the generated framework for optimal shape design based on NRSM. In the future research, we try to apply the optimization problem for Naval Architectural & Ocean Engineering based on the results of this study.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.419-426
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• 2020

The structural design of the steel eccentrically braced frame (EBF) was developed and analyzed in this study through multiobjective optimization (MOO). For the optimal design, NSGA-II which is one of the genetic algorithms was utilized. The amount of structure and interfloor displacement were selected as the objective functions of the MOO. The constraints include strength ratio and rotation angle of the link, which are required by structural standards and have forms of the penalty function such that the values of the objective functions increase drastically when a condition is violated. The regulations in the code provision for the EBF system are based on the concept of capacity design, that is, only the link members are allowed to yield, whereas the remaining members are intended to withstand the member forces within their elastic ranges. However, although the pareto front obtained from MOO satisfies the regulations in the code provision, the actual nonlinear behavior shows that the plastic deformation is concentrated in the link member of a certain story, resulting in the formation of a soft story, which violates the capacity design concept in the design code. To address this problem, another constraint based on the Eurocode was added to ensure that the maximum values of the shear overstrength factors of all links did not exceed 1.25 times the minimum values. When this constraint was added, it was observed that the resulting pareto front complied with both the design regulations and capacity design concept. Ratios of the link length to beam span ranged from 10% to 14%, which was within the category of shear links. The overall design is dominated by the constraint on the link's overstrength factor ratio. Design characteristics required by the design code, such as interstory drift and member strength ratios, were conservatively compared to the allowable values.

• Computational Structural Engineering
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• v.8 no.2
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• pp.123-132
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• 1995

Genetic Algorithms(GA), which are based on the theory of natural evolution, have been evaluated highly for their robust performances. Traditional GA has mostly used binary code for representing design variable. The binary code GA has many difficulties to solve optimization problems with continuous design variables because of its large computer core memory size, inefficiency of its computing time, and its bad performance on local search. In this paper, a real code GA is proposed for dealing with the above problems. So, new crossover and mutation processes of GA are developed to use continuous design variables directly. The results of read code GA are compared with those of binary code GA for several single and multiple objective optimization problems. As a result of comparisons, it is found that the performance of the real code GA is better than that of the binary code GA, and concluded that the real code GA developed here can be used for the general optimization problem.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.9
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• pp.557-567
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• 2016

In this study, the optimal design of heat exchangers, including the evaporator and condenser of a solar-heating ocean thermal energy conversion (SH-OTEC), is investigated. The power output of the SH-OTEC is assumed to be 100 kW, and the SH-OTEC uses the working fluid of R134a and high-performance commercial tubes. The surface heat transfer area and the pressure drop were strongly dependent on the number of tubes, as well as the number of tube passes. To solve the reciprocal tendency between the heat transfer area and pressure drop with respect to the number of tubes, as well as the number of tube passes, a genetic algorithm (GA) with two objective functions of the heat transfer area (the capital cost) and operating cost (pressure drop) was used. Optimal results delineated the feasible regions of heat transfer area and operating cost with respect to the pertinent number of tubes and tube passes. Pareto fronts of the evaporator and condenser obtained from multi-objective GA provides designers or investors with a wide range of optimal solutions so that they can select projects suitable for their financial resources. In addition, the surface heat transfer area of the condenser took up a much higher percentage of the total heat transfer area of the SH-OTEC than that of the evaporator.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.1038-1046
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• 2004

In order to acquire high-speed and high-precision performances in servomechanisms, an integrated design method have been proposed. Based on strict mathematical modeling and analysis of system performance according to design and operating parameters, a nonlinear constrained optimization problem including the relevant subsystem parameters of the servomechanism is formulated. Optimum design results of mechanical and electrical parameters are obtained according to the design parameters specified by designers through the integrated design processes. Motors are optimally selected from the servo motor database. Both the geometric errors referring to Abbe offset and the contour errors are minimized while required constraints such as stability conditions and saturated conditions are satisfied. This design methodology both offers the improved possibility to evaluate and optimize the dynamic motion performance of the servomechanism and improves the quality of the design process to achieve the required performance for high-speed/precision servomechanisms.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.2 s.152
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• pp.139-147
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• 2007

The ultimate goal of structural design is to find the optimal design results which satisfies both safety and economy at the same time. Optimum design has been studied for the last several decades and is being studied. in this study, an optimum algorithm which is based on the genetic algorithm has been applied to the multi-object problem to obtain the optimum solutions which minimizes structural weight and construction cost of panel blocks in ship structures at the same time. Mathematical problems are dealt at first to justify the reliability of the present optimum algorithm. And then the present method has been applied to the panel block model which can be found in ship structures. From the present findings it has been seen that the present optimum algorithm can reasonably give the optimum design results.

• Bulletin of the Society of Naval Architects of Korea
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• v.25 no.1
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• pp.11-20
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• 1988

From the engineering point of view, a synthesis as well as an analysis technique is explored to search for the improved design of grillage which is common in ship structure. As an approximate analysis method for the grillage, an interaction reaction method is developed and compared with the finite element method. It is found that the discrepancy between these two methods is so negligible that the percent method could be used effectively for the grillage analysis. As an optimization technique, a feasible direction method could be used is combined with the intersection reaction method in order to design a minimum weight optimal grillage. The feasible direction method shows a good numerical performance although it requires more calculation times compared with the direct search method. Finally, the application of multiple objective optimization method to grillage is investigated in order to resolve conflicts existed between the multiple objectives which is a common characteristic of structure design problem. Goal programming method is extended to handle a nonlinear property of constraints and objective functions. It seems that the nonlinear goal programming could help not only to establish a relative importance of each objective, but also enable the designer to choose the best combination of design variables.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.2
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• pp.56-64
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• 1996

In this study, a review is made of the previous work(Ref. 1 and 5) for the development of the limit design method of the flat rectangular grillages under the lateral pressure. And the effect of the in-plane loads on the collapse theory is considered. The main part of the work is devoted in developing the standard design method of grillages under the criteria of minimum weight and minimum cost. In the final part, it was shown that Pareto solution methods can be easily applied to structural optimization with the multiple objectives, and the designer can have an appropriate choice from those Pareto optimal solutions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.144-151
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• 2003

In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen fur design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size fur each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem. Favorable solution is obtained by the MLO, which is compared to both solutions made by RSM and sequential quadratic programming (SQP) in the OAO problem.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.539-550
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• 2005

The spanning tree, which is being used the most widely in indoor wiring network, is chosen for the network topology of the optimal LAN design. To apply a spanning tree to GA, the concept of $Pr\ddot{u}fer$ numbers is used. $Pr\ddot{u}fer$ numbers can express he spanning tree in an efficient and brief way, and also can properly represent the characteristics of spanning trees. This paper uses Pareto Stratum-Niche Cubicle(PS-NC) GA by complementing the defect of the same priority allowance in non-dominated solutions of pareto genetic algorithm(PGA). By applying the PS-NC GA to the LAN design areas, the optimal LAN topology design in terms of minimizing both message delay time and connection-cost could be accomplished in a relatively short time. Numerical analysis has been done for a hypothetical data set. The results show that the proposed algorithm could provide better or good solutions for the multi-objective LAN design problem in a fairly short time.