• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.48-57
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• 2009

This paper presents optimal design of direct-driven PM wind generator using MADS (Mesh Adaptive Direct Search). Optimal design of the direct-driven PM Wind Generator, combined with MADS and FEM (Finite Element Method), has been performed to maximize the Annual Energy Production (AEP) over the whole wind speed characterized by the statistical model of the wind speed distribution. In particular, the newly applied MADS contributes to reducing the computation time when compared with Genetic Algorithm (GA) implemented with the parallel computing method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.6
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.583-588
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• 2007

For the purpose of optimum design of RC frame structures. pre-determined section database of column and beam are constructed and arranged in order of the resisting capacity. Then, regression equations representing the relation between section number and resisting capacity are derived. In advance. effective optimization algorithms which search optimized solution quickly using direct search method from these database are proposed. Moreover. the investigation for the applicability and effectiveness of the introduced design procedure is conducted through correlation study for example structures.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.2 s.140
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.571-582
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• 2008

This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.

• Journal of Global Scholars of Marketing Science
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• v.15 no.3
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• pp.93-116
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• 2005

This study explored factors affecting consumer's external information search effort on online shopping malls through three approaches(cost-benefit approach, psychological motivation approach, and web-site theory approach) respectively, and designed the integrative model through searching the relationships among them. In this study search motivation are designed to be explained by search benefit and search cost that are explained by factors related to the web site and search efforts are designed to be explained by search benefit, search cost and search motivation. The results from our empirical research showed that search motivation, search benefits and prior knowledge on online shopping malls have a direct effect on consumer external information search effort. On the other hand, it was verified that the search motivation was affected by search benefits and purchase involvement, and the search benefits are directly influenced by purchase involvement, constructive simplicity, search convenience and trust. In addition, purchase involvement, time press, constructive simplicity and search convenience had direct effects on the search cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.846-855
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• 1992

In this paper, the decrease multipoint search method and Its learning algorithm for optimum value computatlon method of object function Is proposed. Using this method, the number of evaluation point according to searching time can t)e reduced multipoint of the direct search method by applying the unlivarlate method. And the learning algorithm can reprat the same search method in a new established boundary by using the searched result. In order to Investigate the efficience of algorithm, this method this method is applied to Rosenbrock and Powell, Colvelle function that are Impossible or uncertain in traditional direct search method. And the result of application, the optimum value searching oil every function Is successful. Especially, the algorithm is certified as a good calculation method for producing global(absolute) optimum value.

• Journal of the Korean Home Economics Association
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• v.36 no.5
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• pp.29-46
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• 1998

This study investigates how the consumers utilize the elements of information search and how consumers are satisfied with them. For this study, drives who have bought their own cars in two years were chosen for subjects of investigation. And samples were interviewed with an organized questionaire from July 8 to July 27, 1996. 300 samples were used for the final analysis. The major results from this study are as follows. 1) In general information search, consumers get a great deal of information from a talk their friends, neighbors, or colleagues, and they obtain information from an experienced person or a professional. In using sources of information search, they made the best use of their experiences, which is the sources of internal information, and for the second, they used advertising and the explanation of a salesman. In using the contents of information search, they made the best use of information about the merits and demerits in each attribute. In using the method of information search, the mixed search 1 method was used the most, and the attribute search method was used. 2) The casual relationship between the general satisfaction for the products and the relative variable was investigated. An age, the time pressure, the information of the products had a direct and indirect influence on the general for the products. The perceived risk, the number of inquiring activity, a shop and the buying method had a direct influence on the general for the products. An indirect influence was showed in the general satisfaction for the products through the medium of inquiring activity, a shop, and buying method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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• pp.346-353
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• 2005

In this paper, the tension of assembly stay cable connected with massive anchorage block was calculated through back analysis of in-situ frequencies measured from a stadium structure. Direct approach to back analysis is adopted using the univariate method among the direct search methods as an optimization technique. The univariate method can search the optimal tension without regard to the initial ones and has a rapid convergence rate. To verify the reliability of back analysis, Tension formulas proposed by Zui et al. and Shimada were used. Tensions estimated by three methods are compared with the design tension, and are in a reasonable agreement with an error of more or less than 15%. Therefore, it is shown that back analysis applied in this paper is appropriate for estimation of cable tension force.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1549-1557
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• 2018

Optimizing the design of large-scale electric machines based on nonlinear finite element analysis (FEA) requires longer computation time than other applications of FEA, mainly due to the huge size of the machines. This paper addresses a new region decision method (RDM) with mesh adaptive direct search (MADS) for the optimal design of wind generators in order to reduce the computation time. The validity of the proposed algorithm is evaluated using Rastrigin and Goldstein-Price benchmark function. Moreover, the algorithm is employed for the optimal design of a 5.6MW interior permanent magnet synchronous generator to minimize the torque ripple. Additionally, mechanical stress analysis as well as electromagnetic field analysis have been implemented to prevent breakdown caused by large centrifugal forces of the modified design.