• East Asian mathematical journal
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• 제38권3호
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• pp.293-319
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• 2022

In this paper, we introduce a higher order split least-squares characteristic mixed element scheme for Sobolev equations. First, we use a characteristic mixed element method to manipulate both convection term and time derivative term efficiently and obtain the system of equations in the primal unknown and the flux unknown. Second, we define a least-squares minimization problem and a least-squares characteristic mixed element scheme. Finally, we obtain a split least-squares characteristic mixed element scheme for the given problem whose system is uncoupled in the unknowns. We establish the convergence results for the primal unknown and the flux unknown with the second order in a time increment.

• 대한수학회논문집
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• 제19권1호
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• pp.179-196
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• 2004

Mond-Weir type duals for multiobjective variational problems are formulated. Under generalized vector variational type I invexity assumptions on the functions involved, sufficient optimality conditions, weak and strong duality theorems are proved efficient and properly efficient solutions of the primal and dual problems.

• 대한산업공학회지
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• 제10권2호
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• pp.37-43
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• 1984

For the polymatroidal network, which has set-constraints on arcs, solution procedures to get the weighted maximal flows are investigated. These procedures are composed of the transformation of the polymatroidal network flow problem into a polymatroid intersection problem and a polymatroid intersection algorithm. A greedy polymatroid intersection algorithm is presented, and an example problem is solved. The greedy polymatroid intersection algorithm is a variation of Hassin's. According to these procedures, there is no need to convert the primal problem concerned into dual one. This differs from the procedures of Hassin, in which the dual restricted problem is used.

• Korean Journal of Mathematics
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• 제26권3호
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• pp.467-481
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• 2018

In this paper we present a postprocessing scheme for the Raviart-Thomas mixed finite element approximation of the second order elliptic eigenvalue problem. This scheme is carried out by solving a primal source problem on a higher order space, and thereby can improve the convergence rate of the eigenfunction and eigenvalue approximations. It is also used to compute a posteriori error estimates which are asymptotically exact for the $L^2$ errors of the eigenfunctions. Some numerical results are provided to confirm the theoretical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4864-4882
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• 2016

In this work, we consider the optimization problem of minimizing energy consumption for real-time multicast over wireless multi-hop networks. Previously, a distributed primal-dual subgradient algorithm was used for finding a solution to the optimization problem. However, the traditional subgradient algorithms have drawbacks in terms of i) sensitivity to iteration parameters; ii) need for saving previous iteration results for computing the optimization results at the current iteration. To overcome these drawbacks, using a joint network coding and scheduling optimization framework, we propose a novel distributed primal-dual Random Deflected Subgradient (RDS) algorithm for solving the optimization problem. Furthermore, we derive the corresponding recursive formulas for the proposed RDS algorithm, which are useful for practical applications. In comparison with the traditional subgradient algorithms, the illustrated performance results show that the proposed RDS algorithm can achieve an improved optimal solution. Moreover, the proposed algorithm is stable and robust against the choice of parameter values used in the algorithm.

• 대한전기학회논문지:전력기술부문A
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• 제50권10호
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• pp.480-488
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• 2001

This paper presents a technique that can obtain an optimal solution for the Security-Constrained Economic Dispatch (SCED) problems using the Interior Point Method (IPM) while taking into account of the power flow constraints. The SCED equations are formulated by using only the real power flow equations from the optimal power flow. Then an algorithm is presented that can linearize the SCED equations based on the relationships among generation real power outputs, loads, and transmission losses to obtain the optimal solutions by applying the linear programming (LP) technique. The objective function of the proposed linearization algorithm are formulated based on the fuel cost functions of the power plants. The power balance equations utilize the Incremental Transmission Loss Factor (ITLF) corresponding to the incremental generation outputs and the line constraints equations are linearized based on the Generalized Generation Distribution Factor (GGDF). Finally, the application of the Primal Interior Point Method (PIPM) for solving the optimization problem based on the proposed linearized objective function is presented. The results are compared with the Simplex Method and the promising results ard obtained.

• East Asian mathematical journal
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• 제33권3호
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• pp.265-269
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• 2017

In this paper, we formulate a sufficient optimality theorem for the robust optimization problem (UP) under (V, ${\rho}$)-invexity assumption. Moreover, we formulate a Mond-Weir type dual problem for the robust optimization problem (UP) and show that the weak and strong duality hold between the primal problems and the dual problems.

• 전자공학회논문지
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• 제50권8호
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• pp.67-75
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• 2013

OFDM (Orthogonal Frequency Division Multiplexing) 전송방식의 장점은 높은 주파수 효율, RF 간섭에 대한 강인성, 낮은 다중경로 왜곡 등을 들 수 있다. 다중 사용자 OFDM의 채널용량을 확대하기 위해서는 사용자간의 부채널과 비트할당을 위한 효율적인 알고리즘을 개발하여야 한다. 본 연구에서는 다중 사용자 OFDM 시스템에서 총전송전력을 최소화하는 부채널 및 비트 할당을 위한 0-1 정수계획법문제의 선형계획법 dual 문제의 특성을 기존의 볼록최적화기법 접근법과 비교하고 선형계획법 dual 해를 이용한 primal 휴리스틱 알고리즘을 제안한다. MQAM (M-ary Quadrature Amplitude Modulation)을 사용하고 3개의 독립적인 Rayleigh 다중 경로로 구성된 주파수 선택적 채널을 가정한 경우 MATLAB을 사용한 모의실험에서 제안된 휴리스틱 해의 성능을 기존의 MAO, ESA 휴리스틱 해 및 정수계획법 최적해와 성능을 비교하였다.

• Journal of applied mathematics & informatics
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• 제5권2호
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• pp.475-488
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• 1998

Wolfe and Mond-Weir type duals for multiobjective con-trol problems are formulated. Under pseudo-invexity/quasi-invexity assumptions of the functions involved, weak and strong duality the-orems are proved to relate efficient solutions of the primal and dual problems.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제13권3호
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• pp.189-202
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• 2009

In this paper we propose new primal-dual interior point algorithms for $P_*(\kappa)$ linear complementarity problems based on a new class of kernel functions which contains the kernel function in [8] as a special case. We show that the iteration bounds are $O((1+2\kappa)n^{\frac{9}{14}}\;log\;\frac{n{\mu}^0}{\epsilon}$) for large-update and $O((1+2\kappa)\sqrt{n}log\frac{n{\mu}^0}{\epsilon}$) for small-update methods, respectively. This iteration complexity for large-update methods improves the iteration complexity with a factor $n^{\frac{5}{14}}$ when compared with the method based on the classical logarithmic kernel function. For small-update, the iteration complexity is the best known bound for such methods.