• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1020-1023
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• 1998

This paper presents a new approach to large-scale optimal generator maintenance scheduling. To do this, we developed a kind of discrete sensitivity index of each generator by using difference of objective fuction when it is on and off status. Based on the sensitivity value, we applied the conventional priority approach as an optimization method in the order of each generator's sensitivity measure. By applying the developed method, we can efficiently search the state space and dramatically reduce the computation time in a large scale power system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.115-123
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• 1999

An optimization problem is to select the best of many possible design alternatives in a complex design space. Genetic algorithms, one of the numerous techniques to search optimal solution, have been successfully applied to various problems (for example, parameter tuning in expert systems, structural systems with a mix of continuous, integer and discrete design variables) that could not have been readily solved with more conventional computational technique. But, conventional genetic algorithms are ill defined for two classes of problems, ie., penalty function and fitness scaling. Therefore, this paper develops Improved genetic algorithms(IGA) to solve these problems. As a case study, numerical examples are demonstrated to show the effectiveness of the Improved genetic algorithms.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.89-97
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• 2004

The objective of this study is the development of a scheme and discrete optimum design algorithm, which is based on the genetic algorithm. The algorithm can perform both scheme and size optimum designs of plane trusses. The developed Scheme genetic algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. However, its application to the complicated structures has been limited because of the extreme time need for a number of structural analyses. This study solves the problem by introducing the size & scheme genetic algorithm operators into the genetic algorithm. The genetic process virtually takes no time. However, the evolutionary process requires a tremendous amount of time for a number of structural analyses. Therefore, the application of the genetic algorithm to the complicated structures is extremely difficult, if not impossible. The scheme genetic algorithm operators was introduced to overcome the problem and to complement the evolutionary process. It is very efficient in the approximate analyses and scheme and size optimization of plane trusses structures and considerably reduces structural analysis time. Scheme and size discrete optimum combined into the genetic algorithm is what makes the practical discrete optimum design of plane fusses structures possible. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying the algorithm to various optimum design examples: plane pratt, howe and warren truss.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.9
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• pp.17-23
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• 2009

Interest in application of ultraviolet light technology for primary disinfection of potable water in drinking water treatment plants has increased significantly in recent years. The efficacy of disinfection processes in water purification systems is governed by several key factors, including reactor hydraulics, disinfectant chemistry, and microbial inactivation kinetics. The objective of this work was to develop a computational fluid dynamics(CFD) model to predict velocity fields, mass transport, chlorine decay, and microbial inactivation in a continuous flow reactor. The CFD model was also used to evaluate disinfection efficiency in alternative reactor designs. In a typical operation, water enters the inlet of a UV lamp and flows through the annular space between the quartz sleeve and the outside chamber wall. The irradiated water leaves through the outlet nozzle. In this paper, it describe the how to design optimal ultraviolet disinfection device for ground water and rainwater. To search the optimal design method, it was performed computer simulation with 3D-CFD discrete ordinates model and manufactured prototype. Using proposed design method, performed simulation and proved satisfied performance.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.455-460
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• 2009

A number of factors combine to make ultraviolet radiation a superior means of water purification for ground water, rainwater harvesting systems and so on. Ultraviolet radiation is capable of destroying all types of bacteria. Additionally, ultraviolet radiation disinfects rapidly without the use of heat or chemical additives which may undesirably alter the composition of water. In a typical operation, water enters the inlet of a UV lamp and flows through the annular space between the quartz sleeve and the outside chamber wall. The irradiated water leaves through the outlet nozzle. Several design features are combined to determine the dosage delivered. The first is Wavelength output of the lamp, the Second is Length of the lamp - when the lamp is mounted parallel to the direction of water flow, the exposure time is proportional to the length of the lamp, the third is Design water flow rate - exposure time is inversely related to the linear flow rate, the forth is Diameter of the purification chamber - since the water itself absorbs UV energy, the delivered dosage diminishes logarithmically with the distance from the lamp. In this paper, It describe the how to design optimal UV disinfection device for ground water and rainwater. To search the optimal design method, it was performed computer simulation with 3D-CFD discrete ordinates model and manufactured prototype. Using proposed design method manufactured prototype applied to disinfection test and proved satisfied performance.

• Advances in Computational Design
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• v.2 no.4
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• pp.313-331
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• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

• Steel and Composite Structures
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• v.44 no.5
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• pp.603-617
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• 2022

Structural design, in general, is developed through trial and error technique which is guided by standards criteria and based on the intuition and experience of the engineer, a context that leads to structural over-dimensioning, with uneconomic solutions. Aiming to find the optimal design, structural optimization methods have been developed to find a balance between cost, structural safety, and material performance. These methods have become a great opportunity in the steel structural engineering domain since they have as their main purpose is weight minimization, a factor directly correlated to the real cost of the structure. Assuming an objective function of minimum weight with stress and displacement constraints provided by Brazilian standards, the present research proposes the sizing optimization and combined approach of sizing and shape optimization, through a software developed to implement the Simulated Annealing metaheuristic algorithm. Therefore, two steel plane frame layouts, each admitting four typical truss geometries, were proposed in order to expose the difference between the optimal solutions. The assessment of the optimal solutions indicates a notable weight reduction, especially in sizing and shape optimization combination, in which the quantity of design variables is increased along with the search space, improving the efficiency of the optimal solutions achieved.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.11
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• pp.76-88
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• 1998

While most of the research on reinforcement learning assumed a discrete control space, many of the real world control problems need to have continuous output. This can be achieved by using continuous mapping functions for the value and action functions of the reinforcement learning architecture. Two questions arise here however. One is what sort of function representation to use and the other is how to determine the amount of noise for search in action space. The ubiquitous neural network is used here to learn the value and policy functions. Next, the reinforcement predictor that is intended to predict the next reinforcement is introduced that also determines the amount of noise to add to the controller output. The proposed reinforcement learning architecture is found to have a sound on-line learning control performance especially at high-speed road following of high curvature road. Both computer simulation and actual experiments on a test vehicle have been performed and their efficiency and effectiveness has been verified.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.171-181
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• 2008

Home care, known also as domiciliary care, is part of the community care service that is a responsibility of the local government authorities in the UK as well as many other countries around the world. The aim is to provide the care and support needed to assist people, particularly older people, people with physical or learning disabilities and people who need assistance due to illness to live as independently as possible in their own homes. It is performed primarily by care workers visiting clients' homes where they provide help with daily activities. This paper is concerned with the dispatching of care workers to clients in an efficient manner. The optimized routine for each care worker determines a schedule to achieve the minimum total cost (in terms of distance traveled) without violating the capacity and time window constraints. A collaborative population-based meta-heuristic called Particle Swarm Optimization (PSO) is applied to solve the problem. A particle is defined as a multi-dimensional point in space which represents the corresponding schedule for care workers and their clients. Each dimension of a particle represents a care activity and the corresponding, allocated care worker. The continuous position value of each dimension determines the care worker to be assigned and also the assignment priority. A heuristic assignment scheme is specially designed to transform the continuous position value to the discrete job schedule. This job schedule represents the potential feasible solution to the problem. The Earliest Start Time Priority with Minimum Distance Assignment (ESTPMDA) technique is developed for generating an initial solution which guides the search direction of the particle. Local improvement procedures (LIP), insertion and swap, are embedded in the PSO algorithm in order to further improve the quality of the solution. The proposed methodology is implemented, tested, and compared with existing solutions for some 'real' problem instances.

• Journal of the Korean earth science society
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• v.28 no.1
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• pp.87-104
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• 2007

As part of the SPVS (Short-Period Variability Survey) which is a wide-field $(90'{\times}60')$ photometric monitering program at Bohyunsan Optical Astronomy (BOAO), we performed V band time-series CCD photometric observations ofthe young open cluster NGC 129 for 11 nights between October 12, 2004 and November 3, 2005 using the 155mm refractor equipped with $3K{\times}2K$ CCD camera. From the observation we obtained 2400 V band CCD frames and color-magnitude diagram of the cluster. To transform instrumental magnitude to standard magnitude, we applied ensemble normalization technique to all observed time-series data. After the photometric reduction process, we examined variations of 9537 stars. As a result, sixty six of the new variable stars were discovered. To determine the periods of the sevariables, we used DFT(Discrete Fourier Transform) and phase-matching technique. According to light curve shape, period, amplitude and the position on a C-M diagram, we classified these variables as 9 SPB type, 9 ${\delta}$ Scuti type, 29 eclipsing, 17 long term variables. However, two of them were not classified. From this study, we learned that small telescopes could be a very useful tool to observe variable stars in the open cluster in survey program.