• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.58.2-58.2
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• 2011

본 연구에서는 5MW급 수평축 풍력터빈 블레이드에 대해 국내 서남해안의 풍속특성을 고려한 최적설계를 수행 하였다. 최적설계를 수행하기 위해 블레이드 해석은 Blade Element and Momentum Theory를 이용 하였으며, 설계 시 적용된 기저형상은 NREL에서 제안한 5MW급 풍력터빈 블레이드을 선정하였다. 최적설계를 수행하기 전 설계에 사용된 설계변수들이 풍속에 대해 어떠한 경향을 가지고 있는지 알아보기 위해 Parametric Study를 수행 하였으며, 최적설계는 다목적 최적화 유전 알고리즘인 NSGA-II를 이용하여 평균풍속이 낮은 서남해안의 연간에너지 생산량과 설비이용률을 최대화하였다. 최적화 결과들로부터 설계 조건에 맞는 최적해를 도출 할 수 있었으며, 이를 통해 기저형상의 연간에너지 생산량 및 설비이용률을 보다 향상 시킬 수 있었다.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.210-221
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• 2000

Plastic mold designers and frequently faced with optimizing multi-quality issues in injection molded parts. These issues are usually in conflict with each other and thus tradeoff needs to be made to reach a final compromised solution. in this study an automated injection molding design methodology has been developed to optimize multi-quality characteristics of injection molded parts. The features of the proposed methodology are as follows : first utility theory is applied to transform the original multi-objective problem into single-objective problem. Second is an implementation of a direct search-based injection molding optimization procedure with automated consideration of robustness against process variation. The modified complex method is used as a general optimization tool in this study. The developed methodology was applied to an actual mold design and the results showed that the methodology was useful through the CAE simulation using a commercial injection molding software package. Applied to production this study will be of immense value to companies in reducing the product development time and enhancing the product quality.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.131-138
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• 2009

Analytical modal verification is considered as the process to provide an acceptable description of the subject structure's behaviour. In general, results of original analytical model are different with actual structure results to uncertainty like non-linearity of material, boundary and modified shape, etc. In this paper, the dynamic model of glider's wing is correlated with static deformation and vibration test results by goal-attainment method, multi-objects optimization technique. The structural responses are predicted by using finite element method and optimization is carried out by using the SQP(sequential quadratic programming) method which is widely used in the constrained nonlinear optimization problem. The MAC(Modal Assurance Criterion) is used to modify the mode shapes and quantify the similarity.

• Journal of the military operations research society of Korea
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• v.7 no.1
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• pp.118-138
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• 1981

In many response surface optimization problems for industrial processes, there are more than two responses of interest, and we want to find the optimal levels of the factors that influence the responses. This paper is to propose how to set up the desirability functions to find the optimum for a given set of data, and to propose how to analyse the data and the desirability functions to determine an optimal operating condition for the factors. To implement the proposed method in practice, a FORTRAN computer program was written and explained. Finally, an industrial example is illustrated to explain the proposed technique and the source list of the computer program is attached for the users.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.145-152
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• 2004

This paper proposes a representation for the embodiment design of mechanical structures and a genetic algorithm suited for the representation. In order to represent early stages and latter stages of the embodiment design, the designs are modeled as simultaneous multi-objective optimization problems of parametric designs for parts and of layout generation for structures. The study, thus, involves genotypes that are adequate to represent phenotypes of the models for the genetic algorithm to solve the given problems. We demonstrate the implementation of the genetic algorithm with the result applied to the gear equipment design.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.63-79
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• 1994

Many vehicle fleet planning systems have been suggested to minimize the routing distances of vehicles or reduce the transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to vehicle fleet planning system. This paper is considered multi-objective optimization. The vehicle fleet planning system developed by this study involves such complicated and restricted conditions as one depot, multiple nodes (demand points), multiple vehicle types, multipel order items, and other many restrictions for operating vehicles. The proposed algorithm is compared with the nearest neighbor heuristic (NNH) and the savings heuristic (SAH) algorithm in terms of total logistics cost and driving time. This method constructs a route with a minimum number of vehicles for a given demand. This method can be used to any companys which vehicle fleet planning system under circumstances considered in this paper.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.295-300
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• 2002

In conventional model updating using single-objective optimization techniques, incompatible physical data are compared with each other using weighting factors. There are no general rules for selecting the weighting factors since they are not directly related with the dynamic behavior of an updated model. So one of the most difficult tasks, in model updating study, is 'balancing among the correlations' i.e. 'trade-off'. In this work, a multiobjecitive optimization technique called 'satisficing trade-off method' is introduced to extremize several correlations simultaneously. The absurd need for the weighting factors can be avoided using this technique. And the updated model with the most appropriate correlations is obtained easily in interactive way. Especially automatic trade-off is employed to increase the rate of convergence to the desired model. Its effectiveness is verified by application to a real engineering problem, HDD cover model updating.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.513-524
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• 2006

The ammunition allocation problem is a Multi-objective optimization(MOO) problem, maximizing fill-rate of multiple user troops and minimizing transportation time. Recent studies attempted to solve this problem by the prior preference articulation approach such as goal programming. They require that all the preference information of decision makers(DM) should be extracted prior to solving the problem. However, the prior preference information is difficult to implement properly in a rapidly changing state of war. Moreover they have some limitations such as heavy cognitive effort required to DM. This paper proposes a new ammunition allocation model based on more reasonable assumptions and uses an interactive MOO method to the ammunition allocation problem to overcome the limitations mentioned above. In particular, this article uses the GDF procedure, one of the well-known interactive optimization methods in the MOO liter-ature, in solving the ammunition allocation problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.573-576
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• 2006

This paper deals with multi-objective optimization problem of finding a set of well-distributed solutions close to the true Pareto optimal solutions. In this paper, we present a two-leveled symbiotic evolutionary algorithm to efficiently solve the problem. Most of the existing multi-objective evolutionary algorithms (MOEAs) operate one population that consists of individuals representing the complete solution to the problem. The proposed algorithm maintains several populations, each of which represents a partial solution to the entire problem, and has a structure with two levels. The parallel search and the structure are intended to improve the capability of searching diverse and good solutions. The performance of the proposed algorithm is compared with those of the existing algorithms in terms of convergence and diversity. The experimental results confirm the effectiveness of the proposed algorithm.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.266-278
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• 1987

This paper addresses the issues in setting performance criteria for safety regulation of nuclear power plants. Since setting criteria at the low level is a much more difficult task than it is at the top level, the low-level performance criteria should be derived consistently from the more easily determinable top-level performance criteria. The paper also proposes several approaches to characterizing uncertainties in performance criteria, by extending the reliability allocation methodology that is based on the mean-to-mean mapping to a stochastic multi-objective optimization problem where the state variables are uncertain.