• 대한산업공학회지
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• 제17권2호
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• pp.131-142
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• 1991

The concept of criterion function is proposed as a framework for comparing the geometric and computational characteristics of various nonlinear programming approaches to linear programming such as the method of centers, Karmakar's algorithm and the gravitational method. Also, we discuss various computational issues involved in obtaining an efficient parallel implementation of these methods. Clearly, the most time consuming part in solving a linear programming problem is the direction finding procedure, where we obtain an improving direction. In most cases, finding an improving direction is equivalent to solving a simple optimization problem defined at the current feasible solution. Again, this simple optimization problem can be seen as a least squares problem, and the computational effort in solving the least squares problem is, in fact, same as the effort as in solving a system of linear equations. Hence, getting a solution to a system of linear equations fast is very important in solving a linear programming problem efficiently. For solving system of linear equations on parallel computing machines, an iterative method seems more adequate than direct methods. Therefore, we propose one possible strategy for getting an efficient parallel implementation of an iterative method for solving a system of equations and present the summary of computational experiment performed on transputer based parallel computing board installed on IBM PC.

• Journal of applied mathematics & informatics
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• 제26권1_2호
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• pp.349-353
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• 2008

Using the recently developed ABS algorithm for solving linear Diophantine equations we introduce an algorithm for solving a system of m linear integer inequalities in n variables, m $\leq$ n, with full rank coefficient matrix. We apply this result to solve linear integer programming problems with m $\leq$ n inequalities.

• 대한수학교육학회지:학교수학
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• 제8권3호
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• pp.265-290
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• 2006

본 연구의 목적은 엑셀의 활용이 일차함수의 문제해결에 어떤 영향을 미치는가를 알아보는데 있다. 엑셀을 활용한 교수실험 전과 후에 학생들의 함수에 관한 문제해결에서의 변화를 알아보기 위해 사전 사후 문제해결검사를 실시하였다. 문제해결검사 분석은 정확한 과정-대상관점, 근접한 과정-대상관점, 부정확한 과정-대상관점으로 범주화해 이루어졌다. 문제해결검사 분석 결과, 교수실험에 참여한 학생들 모두 일차함수에 관한 문제해결관점이 바람직한 방향으로 변화되었다. 엑셀을 활용한 탐구학습환경이 지필환경의 제한점을 보완할 수 있다는 시사점을 도출하였다.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제24권2호
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• pp.445-474
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• 2010

중학교 1학년 학생들의 일차방정식에 대한 풀이과정에 변화가 있는지를 알아보기 위하여 일차방정식을 학습한 후 1차 조사를 하고, 5개월이 지난 후에 2차 조사를 실시한 결과는 다음과 같다. 첫째, 1차 조사와 2차 조사 간의 정답 비율의 차이를 알아보기 위하여 McNemar검정을 실시한 결과, 유형A의 문항 x+4=9에서 $p=.035^a$, 문항 $x+\frac{1}{4}=\frac{2}{3}$에서 $p=.012^a$로 나타났으며, 유형B의 문항 x+3=8에서 $p=.012^a$, 문항 6(x+20)=20에서 $p=.035^a$으로 나타났다. 둘째, 1차 조사에서 문제 유형A와 유형B의 풀이과정을 올바르게 표현하지 못하였던 학생들 중에 2차 조사에서 올바르게 표현한 학생들이 있는 반면, 1차 조사에서 풀이과정을 올바르게 표현한 학생들 중에 2차 조사에서 오류를 범하는 학생들이 나타났다. 셋째, 모든 문항에 대하여 일차방식의 풀이과정을 올바르게 표현하는 학생들이 있는 반면, 몇 개 문항은 올바르게 표현하고 몇 개 문항은 그렇지 못한 학생들이 있었다. 결론적으로, 주어진 모든 문항에 대한 풀이 과정을 올바르게 표현하였더라도 또 다른 문항이 주어졌을 때 그 문항의 풀이과정에서 올바른 표현을 할 수 있다고 예견하기가 어렵다는 것이다. 논문에서 조사한 세 가지 유형(유형A, 유형B, 유형C)에 대한 학생들의 반응을 분석한 결과에 따르면, 이 세 가지 유형의 문제 풀이과정을 분석함으로써 어떤 학생이 일차방정식의 풀이과정을 올바르게 표현할 수 '있는지', '없는지'를 판단할 수 있다는 것이다.

• 한국경영과학회지
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• 제20권1호
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• pp.147-158
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• 1995

In this paper a face optimization algorithm is developed for solving the problem (P) of optimizing a linear function over the set of efficient solution of a bicriterion linear program. We show that problem (P) can arise in a variety of practical situations. Since the efficient set is in general a nonoconvex set, problem (P) can be classified as a global optimization problem. The algorithm for solving problem (P) is guaranteed to find an exact optimal or almost exact optimal solution for the problem in a finite number of iterations. The algorithm can be easily implemented using only linear programming method.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제27권1호
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• pp.35-42
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• 2020

In this paper, numerical algorithms for solving a fuzzy system of linear equations with crisp coefficients are presented. We illustrate the efficiency and accuracy of the proposed methods by solving some numerical examples. We also provide a graphical representation of the fuzzy solutions in three-dimension as a visual reference of the solution of the fuzzy system.

• Journal of applied mathematics & informatics
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• 제39권3_4호
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• pp.587-600
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• 2021

Some problems in engineering and science can be equivalently transformed into solving multi-linear systems. In this paper, we propose two preconditioned AOR iteration methods to solve multi-linear systems with -tensor. Based on these methods, the general conditions of preconditioners are given. We give the convergence theorem and comparison theorem of the two methods. The results of numerical examples show that methods we propose are more effective.

• 대한수학회논문집
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• 제34권2호
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• pp.657-670
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• 2019

In this paper, we consider the preconditioned iterative methods for solving linear complementarity problem associated with an M-matrix. Based on the generalized Gunawardena's preconditioner, two preconditioned SSOR methods for solving the linear complementarity problem are proposed. The convergence of the proposed methods are analyzed, and the comparison results are derived. The comparison results showed that preconditioned SSOR methods accelerate the convergent rate of the original SSOR method. Numerical examples are used to illustrate the theoretical results.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.802-807
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• 2005

For linear projects, it has long been known that resource utilization is important in improving work efficiency. However, most existing scheduling techniques cannot satisfy the need for solving such issues. This paper presents an optimization model for solving linear scheduling problems involving resource assignment tasks. The proposed model adopts constraint programming (CP) as the searching algorithm for model formulation, and the proposed model is designed to optimize project total cost. Additionally, the concept of outsourcing resources is introduced here to improve project performance.

• 경영과학
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• 제15권1호
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• pp.77-85
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• 1998

In this paper a face optimization algorithm is developed for solving the problem (P) of optimizing a linear function over the set of efficient solutions of a multiple objective linear program. Since the efficient set is in general a nonconvex set, problem (P) can be classified as a global optimization problem. Perhaps due to its inherent difficulty, relatively few attempts have been made to solve problem (P) in spite of the potential benefits which can be obtained by solving problem (P). The algorithm for solving problem (P) is guaranteed to find an exact optimal or almost exact optimal solution for the problem in a finite number of iterations.