• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.179-184
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• 2002

We consider the heterogeneous fleet vehicle routing problem (HVRP), a variant of the classical vehicle routing problem (VRP). The HVRP differs from the classical VRP in that it deals with a heterogeneous fleet of vehicles having various capacities, fixed costs, and variables costs. Therefore the HVRP is to find the fleet composition and a set of routes with minimum total cost. We give an integer programming formulation of the problem and propose an algorithm to solve it. Although the formulation has exponentially many variables, we can efficiently solve the linear programming relaxation of it by using the column generation technique. To generate profitable columns we solve a shortest path problem with capacity constraints using dynamic programming. After solving the linear programming relaxation, we apply a branch-and-bound procedure. We test the proposed algorithm on a set of benchmark instances. Test results show that the algorithm gives best-known solutions to almost all instances.

• 전기학회논문지
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• 제61권11호
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• pp.1682-1688
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• 2012

This paper introduces a GP(Genetic Programming) based robust technique for temperature compensation in short-range prediction. Development of an efficient MOS(Model Output Statistics) is necessary to correct systematic errors of the model, because forecast models do not reliably determine weather conditions. Most of MOS use a linear regression to compensate a prediction model, therefore it is hard to manage an irregular nature of prediction. In order to solve the problem, a nonlinear and symbolic regression method using GP is suggested. The purpose of this study is to evaluate the accuracy of the estimation by a GP based nonlinear MOS for 3 days temperatures in Korean regions. This method is then compared to the UM model and has shown superior results. The training period of 2007-2009 summer is used, and the data of 2010 summer is adopted for verification.

• 대한전기학회논문지
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• 제38권10호
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• pp.805-810
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• 1989

This paper presents a method for planning reactive power compensation such as shunt capacitors and reacters so as to maintain bus voltage in acceptable range during steady state operation in power system. The algorithm in this paper decomposes the problem into reactive power planning module for the compensation of bus voltage and load flow module for adjusting the error resulted from the linear approximation. A planning technique is based on linear programming to minimize the amount of added reactive power compensation in each case. Transformer tap settings and generator voltages are adjusted to minimize the compensation. The constraints are the operation limits of the control variables and bus voltages. The result of one sample system is presented to confirm the practical use of the proposed algorithm.

• 한국인터넷방송통신학회논문지
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• 제21권4호
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• pp.177-182
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• 2021

다양한 원재료를 혼합하여 원하는 성분 함유량을 가진 제품을 최소의 비용으로 생산하는 혼합 최적화 문제에 대해 일반적으로 O(n⁴)의 수행 복잡도의 선형계획법을 적용하고 있다. 본 논문에서는 이 문제에 대해 O(n log n)복잡도로 해를 얻을 수 있는 휴리스틱 알고리즘을 제안한다. 제안된 알고리즘은 합금 강판에서 요구하는 성분들의 함유량 범위를 충족시키면서 최소의 원자재비용을 얻기 위해, 원재료 단가 오름차순으로 성분별 함유량을 충족시키도록 원재료 양을 결정하였다. 3가지 사례에 대해 적용한 결과 제안된 알고리즘은 O(n log n)복잡도로 단순한 결정기법을 적용하였음에도 불구하고, LP의 최적화 기법과 동일하거나 보다 좋은 해를 얻을 수 있었다.

• 대한전기학회논문지:전력기술부문A
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• 제54권3호
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• pp.152-157
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• 2005

An objected-oriented programming(OOP) technique is introduced to dispatch schedules for TWBP. Some dispatch schedules such as constrained (pre)dispatch, unconstrained (pre)dispatch, and nominal self-dispatch schedule need to be peformed to make power market work. These dispatch schedules are similar but have some differences in required constraints, needed data, and scheduling time. Therefore, it makes the scheduling program simple to introduce the OOP technique to this problem: to have each instance of the OOP perform its own dispatch scheduling. The developed program adopts linear programming(LP) as an optimization tool and could consider some crucial constraints such as power balance, generation power limits, generation ramp-rates, power limitations of transmission lines, and power system security.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제22권1호
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• pp.15-28
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• 2018

Recently Machine Learning algorithms are widely used to process Big Data in various applications and a lot of these applications are executed in run time. Therefore the speed of Machine Learning algorithms is a critical issue in these applications. However the most of modern iteration Machine Learning algorithms use a successive iteration technique well-known in Numerical Linear Algebra. But this technique has a very low convergence, needs a lot of iterations to get solution of considering problems and therefore a lot of time for processing even on modern multi-core computers and clusters. Tchebychev iteration technique is well-known in Numerical Linear Algebra as an attractive candidate to decrease the number of iterations in Machine Learning iteration algorithms and also to decrease the running time of these algorithms those is very important especially in run time applications. In this paper we consider the usage of Tchebychev iterations for acceleration of well-known K-Means and SVM (Support Vector Machine) clustering algorithms in Machine Leaning. Some examples of usage of our approach on modern multi-core computers under Apache Spark framework will be considered and discussed.

• 전기의세계
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• 제29권10호
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• pp.660-666
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• 1980

The finite leement method is a effetive analysis technique for obtaining approximate solutions of continuum problems with boundary conditions. This paper deals with the programming for the application of this method and the preciser analysis of the magnetic field in the air gap of the linear stepper motor by the method. The finite element analysis based on the variational principle is adopted and the computer program for reducing input data and a large number of the memory words required by the system matrix is presented. The 2-dimensional analysis of the air gap is made and several cases according to varying the position are considered.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.110-113
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• 1991

An electromagnet is one of the important devices in magnetic levitation system. Its weight takes large part in the total weight of a vehicle. That is the reason why it is important to design the electromagnet optimally to maximize the attraction force with constant volume. This study presents the optimum value of the design variables which can produce the maximal attraction force under constant magnet volume. For this, non-linear programming in optimization technique is used. And to confirm reliability of the results, the optimally designed electromagnet is analyzed by FEM. The attraction force of the optimally designed electromagnet is increased maximally 72% compared with that of the basic model. And the results obtained by non-linear programming has 30% error compared with that of FEM.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.549-552
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• 1996

The tolerance approach to the sensitivity analysis in linear programming considers simultaneous and independent variations in the coefficients of the objective funciton or of the right-hand side terms and gives a region in which the coefficients and terms and gives a region in which the coefficients and terms can be changed and still the current optimal basis B for the original problem remains as an optimal basis for the perturbed problem. In this paper we describe a procedure that expands a region S obtained by the tolerance approch into a larger region R, so that more variations in the objective function coefficients or the right-hand side terms are permissible.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 추계학술대회
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• pp.53-59
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• 2004

Support vector machine(SVM) approach to regression can be found in information science literature. SVM implements the regularization technique which has been introduced as a way of controlling the smoothness properties of regression function. In this paper, we propose a new estimation method based on quadratic loss SVM for a linear fuzzy regression model of Tanaka's, and furthermore propose a estimation method for nonlinear fuzzy regression. This approach is a very attractive approach to evaluate nonlinear fuzzy model with crisp input and output data.