• 호남수학학술지
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• 제35권2호
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• pp.235-249
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• 2013

It is well known that each kernel function defines primal-dual interior-point method (IPM). Most of polynomial-time interior-point algorithms for linear optimization (LO) are based on the logarithmic kernel function ([9]). In this paper we define new eligible kernel function and propose a new search direction and proximity function based on this function for LO problems. We show that the new algorithm has $\mathcal{O}(({\log}\;p)^{\frac{5}{2}}\sqrt{n}{\log}\;n\;{\log}\frac{n}{\epsilon})$ and $\mathcal{O}(q^{\frac{3}{2}}({\log}\;p)^3\sqrt{n}{\log}\;\frac{n}{\epsilon})$ iteration complexity for large- and small-update methods, respectively. These are currently the best known complexity results for such methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.567-568
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• 2007

본 논문에서는 구역별 배전계통운영을 위하여 Non-interior point 배전용 최적조류계산(Distribution non-interior point optimal power flow: NIPDOPF) 알고리즘을 소개한다. NIPDOPF 알고리즘은 향후 지역이나 구역으로 분산전원이 도입될 경우 이를 대비한 영역별 최적조류계산 알고리즘으로 이용할 수 있다.

• 한국실내디자인학회논문집
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• 제18권6호
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• pp.20-27
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• 2009

This study aims to understand the consumer consciousness of the interior design by experiencing the interior space of the model house provided by the construction company. For this, the author investigated the spatial images about the apartment interior design and the satisfaction level depending on the experiential elements. Survey questionnaires were distributed to people who visited six model houses. Subjects were asked about the experience about the interior space of the model house. Their response to the experiential elements was analyzed with 5-point Likert scale and was computed as frequencies, percentages, and means. For the spatial image characteristics, adjectives were substituted for the image scales. As a result, the author found out the following: First, the interior space was commonly directed to the soft image, which was mixed with modern, noble, decent, dynamic and natural styles depending on the companies. The trend of each interior design basically had static, soft and vague images, and partially had two kinds of tendencies: the one was mild and natural, and the other was modern and elegant. Second, as the strategic modules of the experiential marketing, five experiential elements were investigated to find the satisfaction level through the model house interior space. The emotional element got the highest point followed by the cognitive element and the active element, while the sensible element and the relative element got the lowest point. Third, consumer response was generally positive toward the model house interior design provided by the construction company. It is necessary to make up for the design that can give an aesthetic pleasure with familiar images, rather than give a firm recognition about the design.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제12권4호
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• pp.227-238
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• 2008

In this paper we extend primal-dual interior point algorithm for linear optimization (LO) problems to $P_*({\kappa})$ linear complementarity problems(LCPs) ([1]). We define proximity functions and search directions based on kernel functions, ${\psi}(t)=\frac{t^{p+1}-1}{p+1}-{\log}\;t$, $p{\in}$[0, 1], which is a generalized form of the one in [16]. It is the first to use this class of kernel functions in the complexity analysis of interior point method(IPM) for $P_*({\kappa})$ LCPs. We show that if a strictly feasible starting point is available, then new large-update primal-dual interior point algorithms for $P_*({\kappa})$ LCPs have $O((1+2{\kappa})nlog{\frac{n}{\varepsilon}})$ complexity which is similar to the one in [16]. For small-update methods, we have $O((1+2{\kappa})\sqrt{n}{\log}{\frac{n}{\varepsilon}})$ which is the best known complexity so far.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.99-101
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• 2000

Different optimization algorithms have been proposed to solve real and reactive power optimization problems. Most of all, linear programming techniques that employed a simplex method have been extensively used. But, the growth in the size of power systems demands faster and more reliable optimization techniques. An Interior Point(IP) mehod is based on an interior point approach to aim the solution trajectory toward the optimal point and is converged to the solution faster than the simplex method. This paper deals with the use of Successive Linear Programming(SLP) for the solution of the Security Constrained Economic Dispatch(SCED) problem. This problem is solved using the IP method. A comparison with simplex method shows that the interior point technique is reliable and faster than the simplex algorithm.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.24-29
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• 1996

If the LP problem doesn't have the optimal soultion uniquely, the solution fo the primal-dual barrier method converges to the interior point of the optimal face. Therefore, when the optimal vertex solution or the optimal basis is required, we have to perform the additional procedure to recover the optimal basis from the final solution of the interior point method. In this paper the exisiting methods for recovering the optimal basis or identifying the optimal solutions are analyzed and the new methods are suggested. This paper treats the two optimal basis recovery methods. One uses the purification scheme and the simplex method, the other uses the optimal face solutions. In the method using the purification procedure and the simplex method, the basic feasible solution is obtained from the given interior solution and then simplex method is performed for recovering the optimal basis. In the method using the optimal face solutions, the optimal basis in the primal-dual barrier method is constructed by intergrating the optimal solution identification technique and the optimal basis extracting method from the primal-optimal soltion and the dual-optimal solution.

• 한국실내디자인학회논문집
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• 제1호
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• pp.22-25
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• 1992

The purpose of this study is to understand spatial composition techniques and character on the tendency of Deconstructivisim in interior design. Interior space is basically surrounded by architectural surface and influenced by architectural shape. Therefore, the main point of this study is based on the inter relationship of interior design and the trend of contemporary architectural design. This viewpoint is to comment upon current events in Korean situation some degree, but allow the new feeling to interior design and can be enlarge the concepts of spatial composition.

• 한국실내디자인학회:학술대회논문집
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• 한국실내디자인학회 2004년도 추계학술발표대회 논문집
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• pp.177-178
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• 2004

The study will focus on an exploration of a variety of perspectives drawing technique, which is the three-dimensional presentation measure. Through this course, student develop effective expression and introduction of their Interior Design. The contents of the course are as follows : 1. Comprehension of the perspective 2. Comprehension and practice of the 1point perspective 3. Comprehension and practice of the 2point perspective 4. Comprehension and practice of the axonomatrics 5. Practice of the drawing technique through visual note

• 대한수학회논문집
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• 제32권3호
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• pp.765-778
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• 2017

Finding an initial feasible solution on the central path is the main difficulty of feasible interior-point methods. Although, some algorithms have been suggested to remedy this difficulty, many practical implementations often do not use perfectly centered starting points. Therefore, it is worth to analyze the case that the starting point is not exactly on the central path. In this paper, we propose a weighted-path following interior-point algorithm for solving the Cartesian $P_{\ast}({\kappa})$-linear complementarity problems (LCPs) over symmetric cones. The convergence analysis of the algorithm is shown and it is proved that the algorithm terminates after at most $O\((1+4{\kappa}){\sqrt{r}}{\log}{\frac{x^0{\diamond}s^0}{\varepsilon}}\)$ iterations.

• 대한산업공학회지
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• 제28권1호
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• pp.99-104
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• 2002

This paper presents a method of sensitivity analysis for the infeasible interior point method when a new variable is introduced. For the sensitivity analysis in introducing a new variable, we present a method to find an optimal solution to the modified problem. If dual feasibility is satisfied, the optimal solution to the modified problem is the same as that of the original problem. If dual feasibility is not satisfied, we first check whether the optimal solution to the modified problem can be easily obtained by moving only dual solution to the original problem. If it is possible, the optimal solution to the modified problem is obtained by simple modification of the optimal solution to the original problem. Otherwise, a method to set an initial solution for the infeasible interior point method is presented to reduce the number of iterations required. The experimental results are presented to demonstrate that the proposed method works better.