• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.10
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.177-182
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• 2021

Generally, the linear programming (LP) with O(n⁴) time complexity is applied to mixture optimization problem that can be produce the given ingredients grade product with minimum cost from mixture of various raw materials. This paper suggests heuristic algorithm with O(n log n) time complexity to obtain the solution of this problem. The proposed algorithm meets the content range of the components required by the alloy steel plate while obtaining the minimum raw material cost, decides the quantity of raw material that is satisfied with ingredients grade for ascending order of unit cost. Although the proposed algorithm applies simple decision technique with O(n log n) time complexity, it can be obtains same solution as or more than optimization technique of linear programing.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.3
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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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• v.22 no.1
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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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• v.29 no.10
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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.

• Proceedings of the KIEE Conference
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• 1991.07a
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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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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• 2004.10a
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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.