• Korean Journal of Poultry Science
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• v.8 no.1
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• pp.25-30
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• 1981

This study was conducted to find the method that the least-cost formula can be determined thus allowing a better keeping of raw material supplies under the constraints having to be used some raw materials that are either in limited supply or for other reason in restricted use. In this study, it was considered that three kinds of feed were produced under limited supply of six kinds of raw materials, and data for the analysis were collected from a feed mill in southern part of Korea. According to the result of this study, it was proved better to determine the least-cost formula as the multi-mix problem than as the simple least-cost problem when more than two kinds of feed were produced wilt limited supply of raw materials.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.4 s.19
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• pp.61-69
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• 2004

This paper presents a new analytical method for estimating the location of a target using directional data. Based on a nonlinear programming (NLP) problem formulated for the line method, which is a well known algorithm for two-dimensional location estimation, we present a method to find an optimal solution for the problem. Then we present a two-stage method for better location estimation based on the NLP problem. In addition, another two-stage method is presented for location estimation problems in which different types of observers are used to obtain directional data based on the analysis of the maximum likelihood estimate of the target location. The performance of the suggested method is evaluated through simulation experiments, and results show that the two-stage method is computationally efficient and highly accurate.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.23-28
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• 2010

According to increasing projection order, the AP algorithm bas noise amplification problem in large background noise. This phenomenon degrades the performances of the AP algorithm. In this paper, we analyze convergence characteristic of the AP algorithm and then suggest a noise robust modified AP algorithm for reducing this problem. The proposed algorithm normalizes the update equation to reduce noise amplification of AP algorithm, by adding the multiplication of error power and projection order to auto-covariance matrix of input signal. By computer simulation, we show the improved performance than conventional AP algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.75-86
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• 2008

A remarshalling is one of the operational strategies considered importantly at a port container terminal for the fast ship operations and heighten efficiency of slacking yard. The remarshalling rearranges the containers scattered at a yard block in order to reduce the transfer time and the rehandling time of container handling equipments. This Paper deals with the rearrangement problem, which decides to where containers are transported considering time value of each operations. We propose the mixed integer programming model minimizing the weighted total operation cost. This model is a NP-hard problem. Therefore we develope the heuristic algorithm for rearrangement problem to real world adaption. We compare the heuristic algorithm with the optimum model in terms of the computation times and total cost. For the sensitivity analysis of configuration of storage and cost weight, a variety of scenarios are experimented.

• Korean Management Science Review
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• v.34 no.1
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• pp.47-56
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• 2017

We focus on the Real time Fire Scheduling Problem (RFSP), the problem of determining the sequence of targets to be fired at, for the objective of minimizing threatening probability to achieve tactical goals. In this paper, we assume that there are m available weapons to fire at n targets (> m) and the weapons are already allocated to targets. One weapon or multiple weapons can fire at one target and these fire operations should start simultaneously while the finish time of them may be different. We suggest mathematical modeling for RFSP and several heuristic algorithms. Computational experiments are performed on randomly generated test problems and results show that the suggested algorithms outperform the firing method which is generally adopted in the field artillery.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.147-161
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• 1996

Generally the Multiprocessor Scheduling (MPS) problem is difficult to solve because of the precedence of the tasks, and it takes a lot of time to obtain its optimal solution. Though Genetic Algorithm (GA) does not guarantee the optimal solution, it is practical and effective to solve the MPS problem in a reasonable time. The algorithm developed in this research consists of a improved GA and GP/MISF (Critical Path/Most Immediate Successors First). An efficient genetic operator is derived to make GA more efficient. It runs parallel CP/MISF with GA to complement the faults of GA. The solution by the developed algorithm is compared with that of CP/MISF, and the better is taken as a final solution. As a result of comparative analysis by using numerical examples, although this algorithm does not guarantee the optimal solution, it can obtain an approximate solution that is much closer to the optimal solution than the existing GA's.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.16 no.4
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• pp.26-34
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• 2008

This article provides a comprehensive treatment of cracks in non-homogeneous structural materials such as functionally graded materials (FGMs). It is assumed that the material properties depend only on the coordinate perpendicular to the crack surfaces and vary continuously along the crack faces. By using laminated composite plate model to simulate the material non-homogeneity, we present an algorithm for solving the system based on Laplace transform and Fourier transform techniques. Unlike earlier studies that considered certain assumed property distributions and a single crack problem, the current investigation studies multiple crack problem in the FGMs with arbitrarily varying material properties. As a numerical illustration, transient thermal flow intensity factors for a metal-ceramic joint specimen with a functionally graded interlayer subjected to sudden heating on its boundary are presented. The results obtained demonstrate that the present model is an efficient tool in the fracture analysis of non-homogeneous material with properties varying in the thickness direction.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1967-1977
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• 2014

In this paper, for the development of a safe and reliable DC home appliance suitable for DC home power supply system, we classified a number of inherent problems with help of the comparative analysis of existing AC and new DC home appliance. Several new technical problems of DC home appliances are mainly linked to the DC transient state. Among them, this paper concentrates on start-up inrush current problem, uni-polarity problem, and heavy DC load control problem. And to address these problems, we herein present an implementation of robust safety circuits for DC home appliances. Specifically, we investigate several multi-circuit countermeasures and select the best among them through comparative evaluation, based on theoretical, simulational, and experimental results.

• IE interfaces
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• v.25 no.3
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• pp.357-364
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• 2012

This paper considers a unrelated parallel machine scheduling problem with ready times, due times and sequence and machine-dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of machines to minimize the total tardy time. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, a genetic algorithm using an effective dispatching method is proposed. The performance of the proposed genetic algorithm is evaluated using several randomly generated examples.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.447-456
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• 2007

The ant colony optimization (ACO) is a probabilistic Meta-heuristic algorithm which has been developed in recent years. Originally ACO was used for solving the well-known Traveling Salesperson Problem. More recently, ACO has been used to solve many difficult problems. In this paper, we develop an ant colony optimization method to solve the maximum independent set problem, which is known to be NP-hard. In this paper, we suggest a new method for local information of ACO. Parameters of the ACO algorithm are tuned by evolutionary operations which have been used in forecasting and time series analysis. To show the performance of the ACO algorithm, the set of instances from discrete mathematics and computer science (DIMACS)benchmark graphs are tested, and computational results are compared with a previously developed ACO algorithm and other heuristic algorithms.