• East Asian mathematical journal
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• 제26권1호
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• pp.9-23
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• 2010

In this paper we generalize large-update primal-dual interior point methods for linear optimization problems in [2] to the $P_*(\kappa)$ linear complementarity problems based on a new kernel function which includes the kernel function in [2] as a special case. The kernel function is neither self-regular nor eligible. Furthermore, we improve the complexity result in [2] from $O(\sqrt[]{n}(\log\;n)^2\;\log\;\frac{n{\mu}o}{\epsilon})$ to $O\sqrt[]{n}(\log\;n)\log(\log\;n)\log\;\frac{m{\mu}o}{\epsilon}$.

• East Asian mathematical journal
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• 제25권1호
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• pp.55-68
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• 2009

In this paper we propose new large-update primal-dual inte-rior point algorithms for $P_*(\kappa)$ linear complementarity problems(LCPs). New search directions and proximity measures are proposed based on the kernel function$\psi(t)=\frac{t^{p+1}-1}{p+1}+\frac{e^{\frac{1}{t}}-e}{e}$,$p{\in}$[0,1]. We showed that if a strictly feasible starting point is available, then the algorithm has $O((1+2\kappa)(logn)^{2}n^{\frac{1}{p+1}}log\frac{n}{\varepsilon}$ complexity bound.

• Journal of applied mathematics & informatics
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• 제17권1_2_3호
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• pp.351-360
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• 2005

This paper finds a new class of generalized convex function which satisfies the following properties: It's level set is $\eta$-convex set; Every feasible Kuhn-Tucker point is a global minimum; If Slater's constraint qualification holds, then every minimum point is Kuhn-Tucker point; Weak duality and strong duality hold between primal problem and it's Mond-Weir dual problem.

• Journal of applied mathematics & informatics
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• 제17권1_2_3호
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• pp.433-455
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• 2005

Fritz John, and Karush-Kuhn-Tucker type optimality conditions for a constrained variational problem involving higher order derivatives are obtained. As an application of these Karush-Kuhn-Tucker type optimality conditions, Wolfe and Mond-Weir type duals are formulated, and various duality relationships between the primal problem and each of the duals are established under invexity and generalized invexity. It is also shown that our results can be viewed as dynamic generalizations of those of the mathematical programming already reported in the literature.

• 한국경영과학회지
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• 제17권3호
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• pp.59-65
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• 1992

A modified primal-dual affine scaling algorithm for linear programming is presented. This modified algorithm generates an elipsoid containing all optimal dual solutions at each iteration, then checks whether or not a dual hyperplane intersects this ellipsoid. If the dual hyperplane has no intersection with this ellipsoid, its corresponding column must be optimal nonbasic. By condensing these columns, the size of LP problem can be reduced.

• Journal of applied mathematics & informatics
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• 제27권1_2호
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• pp.149-159
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• 2009

In this paper, we introduce some approximate optimal solutions and an augmented Lagrangian function in nonlinear programming, establish dual function and dual problem based on the augmented Lagrangian function, discuss the relationship between the approximate optimal solutions of augmented Lagrangian problem and that of primal problem, obtain approximate KKT necessary optimality condition of the augmented Lagrangian problem, prove that the approximate stationary points of augmented Lagrangian problem converge to that of the original problem. Our results improve and generalize some known results.

• 경영과학
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• 제21권1호
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• pp.77-86
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• 2004

In this paper, we present a methodology for solving the multicommodity network flow problems using interior point methods. In our method, the minimum cost network flow problem extracted from the given multicommodity network flow problem is solved by primal-dual barrier method in which normal equations are solved partially using preconditioned conjugate gradient method. Based on the solution of the minimum cost network flow problem, a warm-start point is obtained from which Castro's specialized interior point method for multicommodity network flow problem starts. In the computational experiments, the effectiveness of our methodology is shown.

• 전기학회논문지
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• 제56권10호
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• pp.1721-1730
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• 2007

SThis paper proposes a new dispatch scheduling algorithm in interconnected regional system operations. The dispatch scheduling formulated as mixed integer non-linear programming (MINLP) problem can efficiently be computed by generalized Benders decomposition (GBD) algorithm. GBD guarantees adequate computation speed and solution convergency since it decomposes a primal problem into a master problem and subproblems for simplicity. In addition, the inter-temporal optimal power flow (OPF) subproblem of the dispatch scheduling problem is comprised of various variables and constraints considering time-continuity and it makes the inter-temporal OPF complex due to increased dimensions of the optimization problem. In this paper, regional decomposition technique based on auxiliary problem principle (APP) algorithm is introduced to obtain efficient inter-temporal OPF solution through the parallel implementation. In addition, it can find the most economic dispatch schedule incorporating power transaction without private information open. Therefore, it can be expanded as an efficient dispatch scheduling model for interconnected system operation.

• 한국경영과학회지
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• 제12권1호
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• pp.34-44
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• 1987

The general vehicle routing problem has been studied by many researchers such as Christofides, et al. and Laporte, et al., but only limited effort has been devoted to developing the optimal algorithms. The purpose of this paper is to develop a branch and bound algorithm which determines the optimal vechicle routes and the optimal number of vehicles concurrenetly for the asymmetrical vehicle routing problem. In order to enhance the efficiency, this algorithm emphasizes the followings ; First, an efficient primal-dual approach is developed to solve subproblems which are called the specialized transportation problem, formed by relaxing the illegal subtour constraints from the vehicle routing problem, second, an improved branching scheme is developed to reduce the number of candidate subproblems by adequate utilization of vehicle capacity restrictions.

• 한국멀티미디어학회논문지
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• 제9권12호
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• pp.1636-1648
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• 2006

In this paper, we propose a new optimization approach to the rate control problem in a wired-cum-wireless network. A primal-dual interior-point(PDIP) algorithm is used to find the solution of the rate optimization problem. We show a comparison between the dual-based(DB) algorithm and PDIP algorithm for solving the rate control problem in the wired-cum-wireless network. The PDIP algorithm performs much better than the DB algorithm. The PDIP can be considered as an attractive method to solve the rate control problem in network. We also present a numerical example and simulation to illustrate our conclusions.