• 대한수학교육학회지:학교수학
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• 제7권2호
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• pp.123-137
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• 2005

순열 조합의 문제는 내재된 의미 구조에 의해 선택, 분배, 분할의 세 가지의 유형으로 분류될 수 있다. 본 연구에서는 순열 조합의 연산과 문제 유형의 변인이 문제의 난이도에 미치는 영향을 분석하였다 그리고 문제 이해과정에서의 오류를 순서, 중복, 대상의 구별, 같은 것이 있는 순열, 상자의 구별, 분할의 조건, 기타로 분류하고 이해 단계의 장애를 구체적으로 분석하였다. 연구 결과, 순열 조합 연산과 문제의 유형은 난이도에 유의미한 영향을 미치는 것으로 나타났다. 특히 학생들에게 선택, 분할, 분배 문제간의 변환은 쉽지 않으며 순열 조합의 문제에서 학생들이 겪는 어려움 중 하나는 바로 문제 유형의 차이에서 비롯된다는 것을 알 수 있었다. 또한 현 교과서에서는 선택, 분배, 분할을 고려한 다양한 문제 유형이 부족한 것으로 나타났다. 따라서 순열 조합의 지도에 있어 문제 유형을 활용하여 다양한 의미 구조의 문제를 제시하고, 공식위주가 아닌 문제 상황을 충분히 이해하고 이에 대한 해법을 변형, 확장하는 경험을 강조하는 것이 필요하다고 하겠다.

• KIEE International Transactions on Power Engineering
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• 제5A권4호
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• pp.331-338
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• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• 접착 및 계면
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• 제10권3호
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• pp.127-133
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• 2009

아크릴 점착제는 고내구성 및 분자량 조절, 관능기의 도입 등이 용이하여 반도체, 디스플레이, 모바일 기기, 자동차 등의 첨단 산업에서 매우 다양하게 활용되고 있다. 점착제의 점착물성은 산업에서의 적용, 공정관리, 제품의 신뢰성에 지대한 영향을 미치기에 그 중요성이 날로 더해가고 있다. 본 연구에서는 조합기법을 이용하여 아크릴 점착제의 물성 영향인자 가운데 두께의 변화에 따른 점착물성 변화를 살펴보고자 한다. 아크릴 점착제는 2-ethylhexyl acrylate와 acrylic acid로 구성된 기본점착제만을 활용하여 샘플을 제작하였으며, 두께 구배가 가능한 micro applicator를 활용하여 thickness-gradient acrylic PSA 샘플을 제작하였으며, 이를 기존의 코팅법으로 제작한 샘플과 비교함으로써 조합기법의 재현성을 평가하였다.

• 대한전기학회논문지:전력기술부문A
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• 제51권5호
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• pp.217-224
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• 2002

This paper presents an algorithm to obtain an approximate optimal solution for the service restoration and load balancing of large scale radial distribution system in a real-time operation environment. Since the problem is formulated as a combinatorial optimization problem, it is difficult to solve a large-scale combinatorial optimization problem accurately within the reasonable computation time. Therefore, in order to find an approximate optimal solution quickly, the authors proposed an algorithm which combines optimization technique called cyclic best-first search with heuristic based feeder loadings balance index for computational efficiency and robust performance. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the KEPCO's 108 bus distribution system.

• 정보처리학회논문지C
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• 제17C권5호
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• pp.399-406
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• 2010

유비쿼터스 네트워크 환경에서 다양한 데이터 서비스가 가능해지면서 악의적인 공격자나 내부 사용자에 의한 보안 취약성 및 프라이버시 침해로 인한 문제를 해결하기 위해 다양한 콘텐츠나 대용량 데이터의 안전한 보안 관리 문제가 주요 이슈로 떠오르고 있다. 기존 다항식 기반을 이용한 Ito, Saito, Nishizeki 할당 방식은 분산된 비밀정보를 복원하기 위해 Share 모두가 필요하게 된다. 반면, 본 제안 방식의 경우, 임계치 이상의 Share가 모아지면 비밀정보를 복원할 수 있다. 또한, 데이터를 분산 복원하는 분산 DBMS 운영상의 효과 특히, 데이터베이스(DB) 서버 및 Share 선택의 규칙성이 있고 조합적 구조인 Combinatorial Design상의 파라메터 t,v,k를 이용함으로써 구현상의 유연성(flexibility)을 갖는다. 본 논문에서는 Share의 할당 문제를 해결하고자 비밀분산 방식을 이용하여 데이터를 분산저장관리 할 때 Share의 할당을 위해 t-(v,k,1) 디자인이 갖는 행렬구조를 적용시킴으로써 새롭게 Share 할당법을 구성하고 데이터 분산저장관리에의 응용에 대해 검토한다.

• Industrial Engineering and Management Systems
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• 제11권4호
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• 한국경영과학회지
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• 제31권3호
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• pp.1-10
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• 2006

In this paper we deal with a cell planning issue arisen in a CDMA based multicast network. In a CDMA based wireless network, a terminal can significantly reduce the bit error rate via the cohesion of data streams from multiple base stations. In this case, multiple base stations have to be operated according to a common time line. The cells whose base stations are operated as such are called soft-combined cells. Therefore, a terminal can take advantage of error rate reduction, if the terminal is in a soft-combined cell and at least one neighboring cell is also soft-combined. However, as soft-combining operation gives heavy burden to the network controller, the limited number of cells can be soft-combined. Our problem us to find a limited number of soft-combined cells such that the benefit of the soft-combining operation is maximized.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1123-1125
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• 1999

This paper proposes an optimization technique using Genetic Algorithm(GA) for service restoration in the distribution system. Restoration planning problem can be treated as a combinatorial optimization problem. So GA is appropriate to solve the service restoration problem in the distribution network. But searching capabilities of the GA can be enhanced by developing relevant repairing operation and modifying GA operations. In this paper, we aimed at finding appropriate open sectionalizing switch position for the restoration of distribution networks after disturbances using enhanced GA with repairing operation and modified mutation. Simulation results show that proposed method found the open sectionalizing switches with less out of service area and minimize transmission line losses and voltage drop.

• 한국시뮬레이션학회논문지
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• 제14권4호
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• pp.1-8
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• 2005

In a metal grating manufacturing process, the cutting operation allocates the gratings and cut them out from given panels or a plate sheets. Before the cutting operation an operator generates a cutting plan. The cutting plan should decide how pieces of metal rectangles i.e., gratings, are allocated and cut from the panel. This plan generation is a deal of weight on the production cost. the generation of cutting plan is similar to the general two-dimensional cutting problem. In this paper, we first define cutting problem and Af algorithm of Artificial Intelligence to solve the problem. Also, through a simulation, we compare the proposed cutting algorithm to an existing method in terms of material loss

• Nuclear Engineering and Technology
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• 제48권2호
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• pp.386-403
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• 2016

The safety of nuclear power plants is analyzed by a probabilistic risk assessment, and the fault tree analysis is the most widely used method for a risk assessment with the event tree analysis. One of the well-known disadvantages of the fault tree is that drawing a fault tree for a complex system is a very cumbersome task. Thus, several graphical modeling methods have been proposed for the convenient and intuitive modeling of complex systems. In this paper, the reliability graph with general gates (RGGG) method, one of the intuitive graphical modeling methods based on Bayesian networks, is improved for the reliability analyses of dynamic systems that have various operation modes with time. A reliability matrix is proposed and it is explained how to utilize the reliability matrix in the RGGG for various cases of operation mode changes. The proposed RGGG with a reliability matrix provides a convenient and intuitive modeling of various operation modes of complex systems, and can also be utilized with dynamic nodes that analyze the failure sequences of subcomponents. The combinatorial use of a reliability matrix with dynamic nodes is illustrated through an application to a shutdown cooling system in a nuclear power plant.