• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.267-272
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• 2015

Active noise control (ANC) is a method of cancelling a noise signal in an acoustic cavity by generating an appropriate anti-noise signal via canceling loudspeakers. The continuous progress of ANC involves the development of improved adaptive signal processing algorithms, transducers, and DSP hardware. In this paper, the convergence behavior and the stability of the FxLMS algorithm in ANC systems with real-time implementation is proposed. Specially, The advanced DSP H/W with dual core(DSP+ARM) and API(application programming interface) S/W programming was developed to improve the real-time implementation performance under the FxLMS algorithms of input noise such as road noise environment. The experimental results are found to be in good agreement with the theoretical predictions.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.274-280
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• 2001

In this research, we develop a specialized primal-dual interior point solver for the multicommodity flow problems (MCFP). The Castro's approach that exploits the problem structure is investigated and several aspects that must be considered in the implementation are addressed. First, we show how preprocessing techniques for linear programming(LP) are adjusted for MCFP. Secondly, we develop a procedure that extracts a network structure from the general LP formulated MCFP. Finally, we consider how the special structure of the mutual capacity constraints is exploited. Results of comupational comparison between our solver and a general interior point solver are also included.

• Management Science and Financial Engineering
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• v.17 no.2
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• pp.1-21
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• 2011

This paper considers an integrated inventory-distribution system with a fleet of heterogeneous vehicles employed where a single warehouse distributes a single type of products to many spatially distributed retailers to satisfy their dynamic demands. The problem is to determine order planning at the warehouse, and also vehicle schedules and delivery quantities for the retailers with the objective of minimizing the sum of ordering cost at the warehouse, inventory holding cost at both the warehouse and retailers, and transportation cost. For the problem, we give a Mixed Integer Programming formulation and develop a Lagrangean heuristic procedure for computing lower and upper bounds on the optimal solution value. The Lagrangean dual problem of finding the best Lagrangrean lower bound is solved by subgradient optimization. Computational experiments on randomly generated test problems showed that the suggested algorithm gives relatively good solutions in a reasonable amount of computation time.

• Kyungpook Mathematical Journal
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• v.47 no.1
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• pp.133-150
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• 2007

In a development of efficient primal-dual interior-points algorithms for self-scaled convex programming problems, one of the important properties of such cones is the existence and uniqueness of "scaling points". In this paper through the identification of scaling points with the notion of "(metric) geometric means" on symmetric cones, we extend several well-known matrix inequalities (the classical L$\ddot{o}$wner-Heinz inequality, Ando inequality, Jensen inequality, Furuta inequality) to symmetric cones. We also develop a theory of spectral geometric means on symmetric cones which has recently appeared in matrix theory and in the linear monotone complementarity problem for domains associated to symmetric cones. We derive Nesterov-Todd inequality using the spectral property of spectral geometric means on symmetric cones.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.1
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• pp.1-11
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• 1999

We classified preprocessing methods into (1) analytic methods, (2) methods for removing implied free variables, (3) methods using pivot or elementary row operations, (4) methods for removing linearly dependent rows and columns and (5) methods for dense columns. We noted some considerations to which should be paid attention when preprocessing methods are applied to interior point methods for linear programming. We proposed an efficient order of preprocessing methods and data structures. We also noted the recovery process for dual solutions. We implemented the proposed preprocessing methods. and tested it with 28 large scale problems of NETLIB. We compared the results of it with those of preprocessing routines of HOPDM, BPDPM and CPLEX.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

• Journal of the Korean Mathematical Society
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• v.47 no.1
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• pp.17-28
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• 2010

In this paper we deal with linear chance-constrained optimization problems, a class of problems which naturally arise in practical applications in finance, engineering, transportation and scheduling, where decisions are made in presence of uncertainty. After giving the deterministic equivalent formulation of a linear chance-constrained optimization problem we construct a conjugate dual problem to it. Then we provide for this primal-dual pair weak sufficient conditions which ensure strong duality. In this way we generalize some results recently given in the literature. We also apply the general duality scheme to a portfolio optimization problem, a fact that allows us to derive necessary and sufficient optimality conditions for it.

• Journal of the Korean Operations Research and Management Science Society
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• v.9 no.2
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• pp.3-8
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• 1984

This paper considers the intermediate warehouse location problem in a two stage distribution system where commodities are delivered from the given set of capacitated factories to customers via uncapacitated intermediate warehouses. In order to determine the subset of warehouses to open which minimizes the total distribution costs including the fixed costs associated with opening warehouses, the cross decomposition method for mixed integer programming recently developed by T.J. Van Roy is used. The cross decomposition unifies Benders decomposition and Lagrangean relaxation into a single framework that involves successive solutions to a primal subproblem and a dual subproblem. In our problem model, primal subproblem turns out to be a transshipment problem and dual subproblem turns out to be an intermediate warehouse location problem with uncapacitated factories.

• IE interfaces
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• v.9 no.3
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• pp.64-71
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• 1996

In the survivability and simplicity aspect, SONET Self-healing Ring(SHR) is one of the most important schemes for the high-speed telecommunication networks. Since the ring capacity requirement is defined by the largest STS-1 cross-section in the ring, load balancing is the key issue in the design of SONET SHR. Recently, most of the research on load balancing problem have been concentrated on the SONET single-ring case. However, in certain applications, multiple-ring configuration is necessary because of the geographical limitations or the need for extra bandwidth. In this paper, the load balancing problem for SONET dual-ring is considered by assuming symmetric inter-ring demands. We present a linear programming based formulation of the problem. Initial solution and improvement procedures are presented, which solves the routing and interconnection between the two rings for each demand. Computational experiments are performed on various size of networks with randomly generated demand sets. Results show that the proposed algorithm is excellent in both the solution quality and the computational time requirement. The average error bound of the solutions obtained is 0.26% of the optimum.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.3-11
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• 1993

We propose a new dual simplex method using a primal interior point. The dropping variable is chosen by utilizing the primal feasible interior point. For a given dual feasible basis, its corresponding primal infeasible basic vector and the interior point are used for obtaining a decreasing primal feasible point The computation time of moving on interior point in our method takes much less than that od Karmarker-type interior methods. Since any polynomial time interior methods can be applied to our method we conjectured that a slight modification of our method can give a polynomial time complexity.