• The KIPS Transactions:PartC
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• v.10C no.2
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• pp.141-144
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• 2003

We present a new password system, called dual password system, with the user verification procedure. Dual password system is the first password system in the world preventing the exposure of secret information to imposter at the terminal. User of dual password system matches two alphabets at same location of first password and second password iteratively for inputting password. Therefore, the deriving method of first password and second password from the password is important in dual password system. Related to the deriving method of first password and second password from password, a new problem, called dual password derivation problem, is defined, and the evaluation factors for the solutions of the dual password derivation problem are presented.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.505-511
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• 2007

Recently, the equivalent relations between a symmetric dual problem and a matrix game B(x, y) were given in [6: D.S. Kim and K. Noh, J. Math. Anal. Appl. 298(2004), 1-13]. Using more simpler form of B(x, y) than one in [6], we establish the equivalence relations between a symmetric dual problem and a matrix game, and then give a numerical example illustrating our equivalence results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.289-292
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• 1996

In Cholesky factorization of the interior point method, dense columns of A matrix make dense Cholesky factor L regardless of sparsity of A matrix. We introduce a method to transform a primal problem to a dual problem in order to preserve the sparsity.

• East Asian mathematical journal
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• v.31 no.3
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• pp.371-377
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• 2015

We consider a nondifferentiable robust optimization problem, which has a maximum function of continuously differentiable functions and support functions as its objective function, continuously differentiable functions as its constraint functions. We prove optimality conditions for the nondifferentiable robust optimization problem. We formulate a Wolfe type dual problem for the nondifferentiable robust optimization problem and prove duality theorems.

• East Asian mathematical journal
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• v.31 no.3
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• pp.345-349
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• 2015

In this paper, we consider a fractional robust optimization problem (FP) and give necessary optimality theorems for (FP). Establishing a nonfractional optimization problem (NFP) equivalent to (FP), we formulate a Mond-Weir type dual problem for (FP) and prove duality theorems for (FP).

• Journal of the Chungcheong Mathematical Society
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• v.26 no.4
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• pp.723-734
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• 2013

A robust optimization problem, which has a maximum function of continuously differentiable functions as its objective function, continuously differentiable functions as its constraint functions and a geometric constraint, is considered. We prove a necessary optimality theorem and a sufficient optimality theorem for the robust optimization problem. We formulate a Wolfe type dual problem for the robust optimization problem, which has a differentiable Lagrangean function, and establish the weak duality theorem and the strong duality theorem which hold between the robust optimization problem and its Wolfe type dual problem. Moreover, saddle point theorems for the robust optimization problem are given under convexity assumptions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2063-2081
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• 2018

A resource allocation algorithm is proposed in this paper to simultaneously minimize the total system power consumption and maximize the system throughput for the downlink of multi-user multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. With the Lagrange dual decomposition method, we transform the original problem to its convex dual problem and prove that the duality gap between the two problems is zero, which means the optimal solution of the original problem can be obtained by solving its dual problem. Then, we use convex optimization method to solve the dual problem and utilize bisection method to obtain the optimal dual variable. The numerical results show that the proposed algorithm is superior to traditional single-objective optimization method in both the system throughput and the system energy consumption.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.308-311
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• 2008

The ant colony optimization (ACO) is a metaheuristic inspired by the behavior of real ants. Recently, ACO has been widely used to solve the difficult combinatorial optimization problems. In this paper, we propose an ACO algorithm to solve the two disjoint paths problem with dual link cost structure (TDPDCP). We propose a dual pheromone structure and a procedure for solution construction which is appropriate for the TDPDCP. Computational comparisons with the state-of-the-arts algorithms are also provided.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.147-156
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• 1993

Recently a new concept of shadow prices, called average shadow price, has been developed. This paper provides a dual problem and the corresponding duality theorems justifying this new shadow price. The general duality framework is used. As an important secondary result, a new reduced class of price function, the pp. h.-class, has been developed for the general duality theory. This should be distinguished from other known reductions achieved in some specific areas of mathematical programming, in that it sustains the strong duality property in all the mathematical programs. The new general dual problem suggested with this pp. h.-class provides, as an optimal solution, the average shadow prices.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.16-26
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• 1989

The terminal layout problem is fundamental in may centralized computer networks, which is generated formulated as the capaciated minimum spanning tree problem (CMSTP). We present an implementation of the dual-based procedure to solve the CMSTP. Dual ascent procedure generates a good feasible solutions to the dual of the linear programming relaxation of CMSTP. A feasible primal solution to CMSTP can then be constructed based on this dual solution. This procedure can be used either as a stand-alone heuristic or, else, it can be incorporated into a branch and bound algorithm. A numerical result is given with quite favorable results.