• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.311-314
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF. To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKP uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Korean Journal of Child Studies
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• v.14 no.1
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• pp.59-75
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• 1993

Based upon the ABC-X model and family systems theory, this study examined (1) problem-solving and behavioral strategies utilized by children in divorced families, and (2) factors related to children's post-divorce adjustment. Date were collected from 158 elementary school aged children and adolescents of divorced families in an urban area (56 male and 102 female). Results of this study indicated that there were significant age differences in problem-solving and behavioral strategies utilized by difficult family situations. Factors that are useful in predicting adjustment of divorced children are the following variables: sex, visitation frequency of noncustodial parent, quality of custodial parent-child communication, and length of divorce. Implications for knowledge as well as recommendations for future research are discussed.

• The Mathematical Education
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• v.48 no.4
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• pp.365-385
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• 2009

Recently, mathematical modeling has been attractive in that it could be one of many efforts to improve students' thinking and problem solving in mathematics education. Mathematical modeling is a non-linear process that involves elements of both a treated-as-real world and a mathematics world and also requires the application of mathematics to unstructured problem situations in real-life situation. This study provides analysis of literature review about modeling perspectives, case studies about mathematical modeling, and textbooks from the United States and Korea with perspective which mathematical modeling could be potential and meaningful to students even in elementary school. Further, teaching method with mathematical modeling was investigated to see the possibility of application to elementary mathematics classroom.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.143-156
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• 2005

Facility location planning (FLP) problem is the strategic level planning in supply chain. The FLP is significantly affected by the operation time of each facility. In most of the FLP researches, operation time of facility has been treated as a fixed value. However, the operation time is not a static factor in real situations and the fixed operation time may lead unrealistic FLP. In this paper, a mixed integer programming (MIP) model is proposed for solving the 3-stage FLP problem and operation times are adjusted by the results from the simulation model and an iterative approach combining the analytic model and simulation model is proposed to obtain more realistic operation plans for FLP problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1020-1025
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• 2005

The set covering(SC) problem has many practical application of modeling not only real world problems in civilian but also in military. In this paper we study optimal allocation model for maximizing utility of consolidating old fashioned and new air defense weapon system like Patriot missile and develop the new computational algorithm for the SC problem by using simulated annealing(SA) algorithm. This study examines three different methods: 1) simulated annealing(SA); 2) accelerated simulated annealing(ASA); and 3) selection by effectiveness degree(SED) with SA. The SED is adopted as an enhanced SA algorithm that the neighboring solutions could be generated only in possible optimal feasible region at the PERTURB function. Furthermore, we perform various experiments for both a reduced and an extended scale sized situations depending on the number of customers(protective objective), service(air defense), facilities(air defense artillery), threat, candidate locations, and azimuth angles of Patriot missile. Our experiment shows that the SED obtains the best results than others.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.343-352
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• 1993

In this study, a modified algorithm for the exchange heuristic is developed and applied to a resource-constrained scheduling problem. The problem involves multiple projects and multiple resource categories and allows flexible resource allocation to each activity. The objective is to minimize the maximum completion time. The exchange heuristkc is a multiple pass algorithm which makes improvements upon a given initial feasible schedule. Four different modified algorithms are proposed. The original algorithm and the new algorithms were compared through an experimental investigation. All the proposed algorithms reduce the maximum completion time much more effectively than the original algorithm. Especially, one of four proposed algorithms obviously outperforms the other three algorithms. The algorithm of the best performance produces significantly shorter schedules than the original algorithm, though it requires up to three times more computation time. However, in most situations, a reduction in schedule length means a significant reduction in the total cost.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.451-456
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• 2007

This paper presents a problem that reconfigure distribution power system using branch exchange method. Optimal reconfiguration problem calculates line loss, voltage condition about system states of all situations that become different according to line On/off status, and search for optimum composition of these. However, result is difficult to be calculated fast. Because radiated operation condition of system is satisfied using many connection and sectionalize switches in the distribution power system. Therefore, in this paper, optimization method for reducing system total loss and satisfying operating condition of radial and constraints condition of voltage is proposed using the fastest branch exchange. And optimal solution at branch exchange algorithm can be wrong estimated to local optimal solution according to initial operating state. Considering this particular, an initial operating point algorithm is added and this paper showed that optimal solution arrives at global optimal solution.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.146-153
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• 2004

This paper presents the method for the placement and operation of dispersed generator systems(DGs) using fuzzy goal programming in distribution systems. For the placement and operation of DGs the problem is formulated with reduction of search spaces and flexibility of system situations. Especially, the original objective function and constraints are transformed by fuzzy goal programming to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.27-37
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• 2007

Many problems related to airline business belong to large-scale optimization problems, so that it is expected that the state-of-art optimization techniques are widely applied to making the airline operation effective and competitive. This paper introduces the concepts and mathematical models of various optimization problems in airline system. Airlines involve many activities that utilize airline resources such as aircrafts and crews to make profit. We view the airline activities in the planning and operational aspects. In the planning viewpoint, we discuss the flight schedule design problem that impacts on passenger demand directly. For aircraft and crews, we deal with fleet assignment, aircraft routing, crew pairing optimization, and crew assignment problem. In the operational viewpoint, we concern schedule recovery problems for aircrafts and crew using the method of reassigning available resources when airlines face with the unexpected situations.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.593-603
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• 2016

This paper presents the development of linear quadratic regulation and output tracking algorithms using output feedback when both the measurement and performance output equations contain direct feedthrough terms. Although all physical systems can be modeled without direct feedthrough, there are still many situations where system models with direct feedthrough are important. For this situation, we modify previous work on the same topic for systems without direct feedthrough. It is shown that for the regulation problem, the optimal output feedback gain for a direct feedthrough case can be directly obtained, via a transformation, from the approach used for systems without direct feedthrough. However, for the tracking problem, a new set of coupled matrix equations for determining the optimal output feedback gain is derived from the necessary conditions for minimizing the cost function. The effectiveness of the developed algorithms is demonstrated using numerical examples.