• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.3
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• pp.478-489
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• 2015

In the present study, a hydrodynamic hull-form optimization algorithm for a container ship was presented in terms of the minimum wave-making resistance. Bell-shaped modification functions were developed to modify the original hull-form and a sequential quadratic programming algorithm was used as an optimizer. The wave-making resistance as an objective function was obtained by the Rankine source panel method in which non-linear free surface conditions and the trim and sinkage of the ship were fully taken into account. Numerical computation was performed to investigate the validity and effectiveness of the proposed hull-form modification algorithm for the container carrier. The computational results were validated by comparing them with the experimental data.

• Structural Engineering and Mechanics
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• v.49 no.4
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• pp.479-489
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• 2014

In the present study a parametric analysis is conducted to study the effect of pile dimension and soil properties on the nonlinear dynamic response of pile subjected to lateral sinusoidal load at the pile head. The study is conducted on soil-pile model of different pile diameter, pile length and soil modulus, and results are compared to get the effect. The soil-pile system is modelled using Finite element method. The programming is done in MATLAB. Time history analysis of model is done for varying non-dimensional frequency of load and the results are compared to get the non-dimensional frequency at which pile head displacement is maximum in each case. Maximum possible bending moment and soil-pile interacting forces for the dynamic excitation of the pile is also compared. When results are compared with the linear response, it is observed that non-dimensional frequency is reduced in nonlinear response on account of reduction in the soil stiffness due to yielding. Nonlinear response curve shows high amplitude as compared to linear response curve.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.247-254
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• 2009

In this study, linear programming was applied to a case study in Gwangreung Experimental Forest of Korea Forest Research Institute investigating the effect of the desired future conditions on forest management. Considering the social, economic and ecological demands of people from the forest, the forest functions were classified into four including natural conservation, timber production, water yield and scenic conservation. The forest land areas were divided into four-types of forest functional zones and forest management prescriptions including the desired future conditions by the forest function type were established. The Model II linear programming was used in optimizing the forest management planning. The model includes management policies, as the constraints, for non-declining yield, allowable cutting area, allowable % age class distribution and allowable % species allocation as well as the land and other accounting regimes. Maximization of timber production was used the objective function. Based on the Model II formulations, the effects of the desired future conditions by the forest function type on forest management planning were investigated in terms of timber production, net present value and stand structures over time.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.18-24
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• 1990

The location of inspection stations is a significant component of production systems. In this paper, a prototype expert system is designed for deciding the optimal location of inspection stations. The production system is defined as a single channel of n serial operation stations. The potential inspection station can be located after any of the operation stations. Nonconforming units are generated from a compound binomial distribution with known parameters at any given operation station. Traditionally Dynamic programming, Zero-one integer programming, or Non-linear programming techniques are used to solve this problem. However a problem with these techniques is that the computation time becomes prohibitively large when t be number of potential inspection stations are fifteen or more. An expert system has the potential to solve this problem using a rule-based system to determine the near optimal location of inspection stations. This prototype expert system is divided into a static database, a dynamic database and a knowledge base. Based on defined production systems, the sophisticated rules are generated by the simulator as a part of the knowledge base. A generate-and-test inference mechanism is utilized to search the solution space by applying appropriate symbolic and quantitative rules based on input data. The goal of the system is to determine the location of inspection stations while minimizing total cost.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.51-61
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• 2003

In the normal equations approach in which the ordering and factorization phases are separated, the factorization in the augmented system approach is computed dynamically. This means that in the augmented system the numerical factorization should be performed to obtain the non-zero structure of Cholesky factor L. This causes much time to set up the non-zero structure of Cholesky factor L. So, we present a method which can separate the ordering and numerical factorization in the augmented system. Experimental results show that the proposed method reduces the time for obtaining the non-zero structure of Cholesky factor L.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.125-127
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• 2003

The Conventional time-domain simulation of transient stability requires iterative calculation procedures to consider the saliency of generator. Recently, a non-iterative algorithm has successfully developed to take into account the generator saliency exactly with the use of $E_q'$-model. This study proposes an extended non-iterative algorithm by adopting the two-axis generator model. Given internal voltages and rotor angles of the generators, network voltages and generator currents can be directly calculated by solving a linear algebraic equation, which enables us to reduce the computation time remarkably.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.709-730
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• 2017

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.149-151
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• 2007

For several decades, VSC has gained much attention as one of the useful design tools for handling the practical system with uncertainties or disturbances. Generally, the disturbances in the matching condition can be perfectly rejected via VSC; however, these in the mismatching condition are known to be hardly rejected. There have been some trials on it, in which the resulting controls in fact belong to the class of robust control guaranteeing disturbance ${\gamma}$-attenuation. Therefore, in this paper, we propose a new Variable Structure Control (VSC) for a system with mismatched disturbances. The proposed controller is composed of linear and nonlinear parts; the former plays a role in stabilizing the system and the latter takes care of attenuating the disturbances. The main contribution is to introduce the concept of switching-zone, rather than switching-surface, that is designed through piece-wise Lyapunov functions. The resulting non-convex conditions are formulated with an iterative linear programming algorithm, which provides an excellent performance of almost rejecting the disturbances.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.47-55
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• 1999

This paper develops an efficient heuristic algorithm for scheduling workforce level that can accommodate all the requested maintenance jobs. Each job has its own release and due dates as well as man-day requirement, and must be scheduled in a non-interrupted time interval, namely, without preemption. Duration of each job is not fixed, but to be determined within given specific range. The objective is to minimize workforce level to complete all the requested maintenance jobs. We show that the problem can be seen as a variant of the two-dimensional bin-packing problem with some additional constraints. A non-linear mixed integer programming model for the problem is developed, and an efficient heuristic algorithm based on bin-packing algorithms is proposed. In order to evaluate goodness of the solution obtained from the proposed algorithm, a scheme for getting a good lower bound for the optimum solution is presented and analyzed. The computational experiment shows that the proposed algorithm performs quite satisfactorily.