• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.8
• /
• pp.790-797
• /
• 2007

This paper proposes a new measure of cost function ruggedness in local optimization with DEAS. DEAS is a computational optimization method developed since 2002 and has been applied to various engineering fields with success. Since DEAS is a recent optimization method which is rarely introduced in Korean, this paper first provides a brief overview and description of DEAS. In minimizing cost function with this non-gradient method, information on function shape measured automatically will enhance search capability. Considering the search strategies of DEAS are well designed with binary matrix structures, analysis of search behaviors will produce beneficial shape information. This paper deals with a simple quadratic function contained with various magnitudes of noise, and DEAS finds local minimum yielding ruggedness measure of given cost function. The proposed shape information will be directly used in improving DEAS performance in future work.

• Journal of Korean Institute of Industrial Engineers
• /
• v.1 no.2
• /
• pp.39-49
• /
• 1975

The problem treated is that of locating distribution centers(depot) in a network, so as to minimize the total cost which is the sum of transportation cost, (from factory to centers and from centers to demand points), construction cost, inventory cost and traffic increasing cost. This problem is mathematically an integer program and a non-linear model. This study avoids various inefficient aspects, which many studies have shown, by introducing a matrix notation, node and link function. An algorithm, for determining the optimal location of distribution center which has zone in which demand points are located at some node of a network, is presented. Finally this paper describes a numerical example and discusses its results.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.8
• /
• pp.1429-1433
• /
• 2008

In this paper, we consider the design method of robust guaranteed cost controller for discrete-time singular systems with norm-bounded time-varying parameter uncertainty. In order to get the optimum(minimum) value of guaranteed cost, an optimization problem is given by linear matrix inequality (LMI) approach. The sufficient condition for the existence of controller and the upper bound of guaranteed cost function are proposed in terms of strict LMIs without decompositions of system matrices. Numerical examples are provided to show the validity of the presented method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.8
• /
• pp.1491-1497
• /
• 2007

This paper considers robust and non-fragile guaranteed cost controller design method for descriptor systems with parameter uncertainties and time delay, and static state feedback controller with gain variations. The existence condition of controller, the design method of controller, the upper bound to minimize guaranteed cost function, and the measure of non-fragility in controller are proposed using linear matrix inequality (LMI) technique, which can be solved efficiently by convex optimization. Therefore, the presented robust and non-fragile guaranteed cost controller guarantees the asymptotic stability and non-fragility of the closed loop systems in spite of parameter uncertainties, time delay, and controller fragility.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.1
• /
• pp.196-205
• /
• 1996

Severice allocation to satellite transponders under consideration of interference caused by inter-satellite and intra-satellite systems is one of the most important issue in terms of optimal usage of satellite network resource. In this paper, we present a new and show several simulation results to verify the proposed method. Especially, our concerns are concentrated on the cost (interference) matrix which is believed to be optimal in obtaining the service allocation plan. The method and concepts presented in this paper may be well applicable to making a plan for service assignment of the satellite communication systems.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.1
• /
• pp.105-114
• /
• 2009

Recently, location-based services which provides k nearest POIs, e.g., gas stations, restaurants and banks, are essential such applications as telematics, ITS(Intelligent Transport Systems) and kiosk. For this, the Voronoi Diagram k-NN(Nearest Neighbor) search algorithm has been proposed. It retrieves k-NNs by using a file storing pre-computed network distances of POIs in Voronoi diagram. However, this algorithm causes the cost problem when expanding a Voronoi diagram. Therefore, in this paper, we propose an algorithm which generates a matrix of the shortest distance between border points of a Voronoi diagram. The shortest distance is measured each border point to all of the rest border points of a Voronoi Diagram. To retrieve desired k nearest POIs, we also propose a k-NN search algorithm using the matrix of the shortest distance. The proposed algorithms can m inim ize the cost of expanding the Voronoi diagram by accessing the pre-computed matrix of the shortest distances between border points. In addition, we show that the proposed algorithm has better performance in terms of retrieval time, compared with existing works.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.9B
• /
• pp.914-922
• /
• 2009

In this paper, we propose a matrix based real-time pattern matching method, called MDPI, for real-time intrusion detection on several Gbps network traffic. Particularly, in order to minimize a kind of overhead caused by buffering, reordering, and reassembling under the circumstance where the incoming packet sequence is disrupted, MDPI adopts independent partial matching in the case dealing with pattern matching matrix. Consequently, we achieved the performance improvement of the amount of 61% and 50% with respect to TCAM method efficiency through several experiments where the average length of the Snort rule set was maintained as 9 bytes, and w=4 bytes and w=8bytes were assigned, respectively, Moreover, we observed the pattern scan speed of MDPI was 10.941Gbps and the consumption of hardware resource was 5.79LC/Char in the pattern classification of MDPI. This means that MDPI provides the optimal performance compared to hardware complexity. Therefore, by decreasing the hardware cost came from the increased TCAM memory efficiency, MDPI is proven the cost effective high performance intrusion detection technique.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.6 no.1
• /
• pp.25-32
• /
• 1981

The optimum design problem of a proposed oil pipeline network has been formulated as a zero-one programming model to determine the optimum sizes of pipe and pump which minimize the sum of material costs and operating costs during the 20 years of life span. Applying to a real situation, the problem constitutes an assignment type zero-one programming with 372 zero-one variables and 13 constraints. A heuristic algorithm has been developed based on the modified Petersen algorithm utilizing the special form of the activity matrix. The results showed impressive cost savings of 37 percent of the total cost from the original proposal.

• Journal of the Microelectronics and Packaging Society
• /
• v.8 no.2
• /
• pp.49-52
• /
• 2001

This paper presents product level considerations for multichip packaging as a cost effective alternative to single chip packaging in the design and manufacture of mobile telephony products. Important aspects include component functionality and complexity, acquisition and logistics costs, product modularity and integration. Multichip packaging offers unique solutions and significant system level cost savings in many applications including RF modules, digital matrix functions and product options such as security, data storage, voice recognition, etc.

• Communications of the Korean Mathematical Society
• /
• v.9 no.2
• /
• pp.449-465
• /
• 1994

The two common numerical methods to approximate the solution of partial differential equations are the finite element method and the finite difference method. They both lead to solving large sparse linear systems. For many applications, it is not unusal that the order of matrix is greater than 10, 000. For this kind of problem, a direct method such as Gaussian elimination can not be used because of the prohibitive cost. To this end, many iterative methods with modest cost have been studied and proposed by numerical analysts.(omitted)