• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 B
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• pp.577-579
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• 1992

A new algorithm, which combines the Evolution Strategy and the Simplex method, is proposed for the detection of magnetic body utilizing the disturbance of magnetic fields. Although the detection problem of magnetic body which belongs to the inverse problem may have many local minima, the global optimum point was found by introducing the Evolution Strategy. And the convergency rate was enhanced by introducing the Simplex method. Through the numerical examples, the applicability and usefulness of the proposed algorithm are proved.

• Journal of Hydrospace Technology
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• 제2권2호
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• pp.24-35
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• 1996

This paper describes parameter identification techniques formulated for the estimation of maneuvering coefficients of a submerged body. The first part of this paper is concerned with the identifiability of the system parameters. The relationship between a stochastic linear time-invariant system and the equivalent dynamic system is investigated. The second is concerned with the development of the numerically stable identification technique. Two identification techniques are tested; one is the ma7mum likelihood (ML) methods using the Holder & Mead simplex search method and using the modified Newton-Raphson method, and the other is the modified extended Kalman filter (MEKF) method with a square-root algorithm, which can improve the numerical accuracy of the extended Kalman filter. As a results, it is said that the equations of motion for a submerged body have higher probability to generate simultaneous drift phenomenon compared to general state equations and only the ML method using the Holder & Mead simplex search method and the MEKF method with a square-root algorithm gives acceptable results.

• 경영과학
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• 제15권1호
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• pp.1-12
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• 1998

This paper discusses a new algorithm, the PAPANET (Pivot And Probe Algorithm for NETwork optimization), for solving linear, capacitated linear network flow problem (NPs), PAPANET is a variation and specialization of the Pivot And Probe Algorithm (PAPA) developed by Sethi and Thompson, published in 1983-1984. PAPANET first solves an initial relaxed NP (RNP) with all the nodes from the original problem and a limited set of arcs (possibly all the artificial and slack arcs). From the arcs not considered in the current relaxation, we PROBE to identify candidate arcs that violate the current solution's dual constraints maximally. Candidate arcs are added to the RNP, and this new RNP is solved to optimality. This candidate pricing procedure and pivoting continue until all the candidate arcs price unfavorably and all of the dual constraints corresponding to the other, so-called noncandidate arcs, are satisfied. The implementation of PAPANET requires significantly fewer arcs and less solution CPU time than is required by the standard network simplex method implementation upon which it is based. Computational tests on randomly generated NPs indicate that our PAPANET implementation requires up to 40-50% fewer pivots and 30-40% less solution CPU time than is required by the comparable standard network simplex implementation from which it is derived.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.859-865
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• 2014

Optimization of an electric machine is mainly a nonlinear multi-modal problem. For the optimization of the multi-modal problem, many function calls are required with much consumption of time. To address this problem, this paper proposes a novel hybrid algorithm in which function calls are less than conventional methods. Specifically, the proposed method uses the kriging metamodel and the fill-blank technique to find an approximated solution in a whole problem region. To increase the convergence speed in local peaks, a parallel gradient assisted simplex method is proposed and combined with the kriging meta-model. The correctness and usefulness of the proposed hybrid algorithm is verified through a mathematical test function and applied into the practical optimization as the cogging torque minimization for an interior permanent magnet synchronous machine.

• 한국경영과학회지
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• 제19권3호
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• pp.187-201
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• 1994

This paper introduces an effective hybridization of the usual simplex method and an interior point method in the convergent framework of Dembo and Sahi. We formulate a specific and detailed algorithm (HYBRID) and report the results of some preliminary testing on small dense problems for its viability. By piercing through the feasible region, the newly developed hybrid algorithm avoids the combinatorial structure of linear programs, and several other interesting and important characteristics of this algorithm are also discussed.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1998년도 The Korea Society for Simulation 98 춘계학술대회 논문집
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• pp.11-16
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• 1998

The classical algorithm for solving liner network flow problems are primal cost improvement method, including simplex method, which iteratively improve the primal cost by moving flow around simple cycles, which iteratively improve the dual cost by changing the prices of a subset of nodes by equal amounts. Typical iteration/shortest path algorithm is used to improve flow problem of liner network structure. In this paper we stdudied about the implemental method of shortest path which is a practical computational aspects. This method can minimize the best neighbor node and also implement the typical iteration which is $\varepsilon$-CS satisfaction using the auction algorithm of linear network flow problem

• 물과 미래
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• 제27권1호
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• pp.111-121
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• 1994

본 연구의 목적은 한정된 자료원을 각 용수 수요점 별로 용수공급 우선 순위에 따라서 최적배분하기 위한 Network 모형을 구성하는 것이다. 본 모형의 해법은 OKA(Out of Kilter Algorithm)를 사용하였다. 모형에 대한 이론적 방법론과 프로그램을 검증하고 적용하기 위하여 금강유역을 선정했다. 대청댐 방유량과 금강 유역의 용수수요량을 사용하여, 각 수요점의 용수공급 우선 순위를 1~ 4개의 경우로 설정하고 수자원의 최적배분을 시행하였다. 모형을 적용한 결과, 물리적인 시스템을 타당성 있게 표현할 수 있었고, 높은 우선 순위로 조정된 수요점에서는 물 부족량을 줄일 수 있었다. 본 모형의 해법은 Revised Simplex 알고리즘에 의해 검증하였다.

• 산업경영시스템학회지
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• 제21권45호
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• pp.93-100
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• 1998

The researches of Linear Programming are Khachiyan Method, which uses Ellipsoid Method, and Karmarkar, Affine, Path-Following and Interior Point Method which have Polynomial-Time complexity. In this study, Karmarkar Method is more quickly solved as 50 times then Simplex Method for optimal solution. but some special problem is not solved by Karmarkar Method. As a result, the algorithm by APL Language is proved time efficiency and optimal solution in the Primal-Dual interior point algorithm. Furthermore Karmarkar Method and Primal-Dual interior point Method is compared in some examples.

• 한국정보과학회논문지:시스템및이론
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• 제32권3호
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• pp.133-147
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• 2005

LCD BLU(Back-Light Unit)의 설계에는 광선추적 기법이 많이 사용되고 있으며, 이러한 기법을 통하여 도광판 전면으로 출사되는 빛의 휘도, 휘도의 균일도, 광효율 등을 수치적으로 예측할 수 있다. 휘도와 휘도의 균일도 등과 같은 항목은 BLU 설계에 있어서 매우 중요한 요소 중의 하나이며, 이러한 BLU의 광학적 특성은 도광판의 후면에 인쇄된 잉크패턴에 가장 많을 영향을 받고 있다 따라서 높은 휘도와 균일도를 발생시킬 수 있는 최적화된 잉크패턴을 설계하는 것은 BLU의 설계에 있어서 가장 중요한 부분 중의 하나이다. 본 논문에서는 최적의 잉크패턴을 설계하기 위하여 직접탐색(Direct Search) 기법 중에서 Holder Mead의 심플렉스탐색(Simplex Search) 알고리즘을 적용하였다. 직접탐색 기법은 최적의 잉크패턴을 계산하는 것과 같은 비선형적이고, 비연속적이며, 미분불가능한 함수의 최적점을 계산하는 분야에 많이 적용되고 있다. 본 논문에서는 여러 가지 실험을 통하여 심플렉스탐색 기법이 최적의 잉크패턴을 설계하는데 있어서 매우 효율적이며 안정적으로 사용될 수 있음을 보여주며, 이러한 최적화 기법으로 인하여 BLU 설계기능을 개선할 수 있음을 보여준다

• 한국멀티미디어학회논문지
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• 제7권11호
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• pp.1531-1539
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• 2004

본 논문은 입술의 경계선을 효과적으로 추출하는 방법을 제안하였다. 입술 형태는 PDM(Point Distribution Model)과 주성분 분석법을 이용하여 표현하고 입술 경계선은 GLDM(Gray Level Distribution Model)을 기반으로 표현하였다 입술 경계선 추출은 모델에 대한 입력영상의 정확도에 대한 목적함수를 최적화하는 문제로 단순화하였으며, 최적화를 위해 다운힐 심플렉스(Down Hill Simplex) 알고리즘을 이용하였다. 탐색과정에서 지역 최소점으로 수렴하는 문제를 해결하기 위하여 입술 형태 모델의 형태계수를 GMM(Gaussian Mixture Model)을 이용하여 표현하였다. 형태계수에 대한 GMM을 이용하여 입술의 대략적인 형태를 찾고, 이때 사용된 mixture 성분을 이용하여 탐색과정에서 입술의 형태를 조정함으로써 지역 최소점에 수렴하여 입술의 정확한 위치를 찾지 못하는 문제점을 해결하였다. 여러 영상을 대상으로 실험하여 좋은 결과를 얻었다.