• 전기의세계
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• v.21 no.3
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• pp.48-52
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• 1972

The application of pontryagin's Maximum Principle to the optimal control eventually leads to the problem of solving the two point boundary value problem. Most of problems have been related to their own special factors, therfore it is very hard to recommend the best method of deriving their optimal solution among various methods, such as iterative Runge Kutta, analog computer, gradient method, finite difference and successive approximation by piece-wise linearization. The gradient method has been applied to the optimal control of two point boundary value problem in the power systems. The most important thing is to set up some objective function of which the initial value is the function of terminal point. The next procedure is to find out any global minimum value from the objective function which is approaching the zero by means of gradient projection. The algorithm required for this approach in the relevant differential equations by use of the Runge Kutta Method for the computation has been established. The usefulness of this approach is also verified by solving some examples in the paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.652-658
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• 1998

We introduce the concept of a bi-population scheme for real-coded GAs consisting of an explorer sub-Ga and an exploiter sub-GA. The explorer sub-GA mainly performs global exploration of the search space, and incorporates a restart mechanism to help avoid being trapped at local optima. The exploiter sub-GA performs exploitation of fit local areas of the search space around the neighborhood of the best-so-far solution. Thus the search function of the algorithm is divided. the proposed technique exhibits performance significantly superior to standard GAs on two complex highly multimodal problems.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1328-1333
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• 2007

Unpredictable customer demands make manufacturers to make quality products with cheaper price and shorter delivery. To survive in the global market, the manufacturing industry needs to equip with advanced technologies including IT. Under this situation, "collaboration"is the best solution for manufacturers to survive and to grow their company instead of competition. With this strategy, we have conducted a project(e-Manufacturing). The companies participate to the project attained the amazing results by utilizing collaboration systems such as delivery shortened and increase in sale/profit. Since the strategy of the project is assessed to be very useful to increase competition power of manufacturers, the project will be enlarged to cover wider application domains with a new project name called "i-Manufacturing". In this paper, therefore, we introduce the specific output from the e-Manufacturing project and the specific strategies/plans of i-Manufacturing project.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.1
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• pp.55-66
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• 2001

The Global Positioning System(GPS) and the Strapdown Inertial Navigation System(SDINS) techniques have been widely utilized in many applications. However each system has its own weak point when used in a stand-alone mode. SDINS suffers from fast error accumulation dependent on an operating time while GPS has problem of cycle slips and just provides low update rate. The best solution is to integrate the GPS and SDINS system and its integration allows compensation for each shortcomings. This paper, first, is to define and derive error equations of integrated SDINS/GPS system before it will be applied on a real hardware system with gyro, accelerometer and GPS receiver. Second, the accuracy, availability and performance of this mechanization are verified on the simulation study.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.210-223
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• 2020

Since constrained optimization algorithms are easy to fall into local optimum and their ability of searching are weak, an improved symbiotic organisms search algorithm with mixed strategy based on adaptive ε constrained (ε_SOSMS) is proposed in this paper. Firstly, an adaptive ε constrained method is presented to balance the relationship between the constrained violation degrees and fitness. Secondly, the evolutionary strategies of symbiotic organisms search algorithm are improved as follows. Selecting different best individuals according to the proportion of feasible individuals and infeasible individuals to make evolutionary strategy more suitable for solving constrained optimization problems, and the individual comparison criteria is replaced with population selection strategy, which can better enhance the diversity of population. Finally, numerical experiments on 13 benchmark functions show that not only is ε_SOSMS able to converge to the global optimal solution, but also it has better robustness.

• Genomics & Informatics
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• v.19 no.2
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• pp.13.1-13.8
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• 2021

Ranked in the topmost position among the deadliest diseases in the world, cardiovascular diseases (CVDs) are a global burden with alterations in heart and blood vessels. Early diagnostics and prognostics could be the best possible solution in CVD management. OMICS (genomics, proteomics, transcriptomics, and metabolomics) approaches could be able to tackle the challenges against CVDs. Genome-wide association studies along with next-generation sequencing with various computational biology tools could lead a new sight in early detection and possible therapeutics of CVDs. Human cardiac proteins are also characterized by mass spectrophotometry which could open the scope of proteomics approaches in CVD. Besides this, regulation of gene expression by transcriptomics approaches exhibits a new insight while metabolomics is the endpoint on the downstream of multi-omics approaches to confront CVDs from the early onset. Although a lot of challenges needed to overcome in CVD management, OMICS approaches are certainly a new prospect.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.117-126
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• 2003

GA(genetic algorithm) has a powerful searching ability and is comparatively easy to use and to apply as well. By that reason, GA is in the spotlight these days as an optimization skill for mechanical systems.$^1$However, GA has a low efficiency caused by a huge amount of repetitive computation and an inefficiency that GA meanders near the optimum. It also can be shown a phenomenon such as genetic drifting which converges to a wrong solution.$^{8}$ These defects are the reasons why GA is not widdy applied to real world problems. However, the low efficiency problem and the meandering problem of GA can be overcomed by introducing parallel computation$^{7}$ and gray code$^4$, respectively. Standard GA(SGA)$^{9}$ works fine on small to medium scale problems. However, SGA done not work well for large-scale problems. Large-scale problems with more than 500-bit of sere's have never been tested and published in papers. In the result of using the SGA, the powerful searching ability of SGA doesn't have no effect on optimizing the problem that has 96 design valuables and 1536 bits of gene's length. So it converges to a solution which is not considered as a global optimum. Therefore, this study proposes ExpGA(experience GA) which is a new genetic algorithm made by applying a new probability parameter called by the experience value. Furthermore, this study finds the solution throughout the whole field searching, with applying ExpGA which is a optimization technique for the structure having genetic drifting by the standard GA and not making a optimization close to the best fitted value. In addition to them, this study also makes a research about the possibility of GA as a optimization technique of large-scale design variable problems.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.435-447
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• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• International Commerce and Information Review
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• v.11 no.4
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• pp.395-418
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• 2009

Appeared in the 1970s he started the global warming problem of carbon reduction, unlike the expected withdrawal of the United States was anticipated to be nominal stripping. However, EU mainly carbon market, buy and sell rights to be disposed of evolution was born. In fact, the current reduction of the Kyoto Protocol, and Korea will be designated as the bureau had been scheduled. However, due to economic recession in Korea's status as exempt countries have enjoyed a considerable period. Global warming is a problem in earnest, however, the United States to participate in one or more such discussions since 2013, clearly this will begin the international order. And international order that is more stringent than expected, and is expected to be strong. Then, however, an interesting thing to justify protection of the environment in some countries to protect domestic industry, the movement is visible is the side. In fact the WTO since the conclusion of all non-tariff trade barriers were abolished. However, recently, New Round of the delay based on reciprocity and fair trade in the framework of environmental protection to justify the movement to protect the domestic industry has been captured. These trends are not friendly, never in Korea. The rationale is that these regulations are enforced, many of our countries and countries with significant trade transactions and the enforcement points. And South Korea's automotive, semiconductors, ships, etc. The main products are much discussed in the international regulations are being referred to as the target point is due. Korean government to actively participate in the international situation and efforts to explore new markets, said yesterday, and 'Low Carbon, Green Growth' was declared. And the Intergovernmental Panel on Climate Change(IPCC) recommendations of the best 30% reduction target was present. This is nothing different about this objection is true. A more fundamental solution to faithfully perform the reduction targets, while the development of environmentally friendly products and the incidence of international standards through the development and expansion of new growth engines, Indeed we are expected to be a fundamental methodology.

• International Journal of Highway Engineering
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• v.20 no.3
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• pp.59-64
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• 2018

PURPOSES : We propose a parameter-setting-free harmony-search (PSF-HS) algorithm to determine the individual sound power levels of noise sources in the cases of industrial or road noise environment. METHODS :In terms of using methods, we use PSF-HS algorithm because the optimization parameters cannot be fixed through finding the global minimum. RESULTS:We found that the main advantage of the PSF-HS heuristic algorithm is its ability to find the best global solution of individual sound power levels through a nonlinear complex function, even though the parameters of the original harmony-search (HS) algorithm are not fixed. In an industrial and road environment, high noise exposure is harmful, and can cause nonauditory effects that endanger worker and passenger safety. This study proposes the PSF-HS algorithm for determining the PWL of an individual machine (or vehicle), which is a useful technique for industrial (or road) engineers to identify the dominant noise source in the workplace (or road field testing case). CONCLUSIONS : This study focuses on providing an efficient method to determine sound power levels (PWLs) and the dominant noise source while multiple machines (or vehicles) are operating, for comparison with the results of previous research. This paper can extend the state-of-the-art in a heuristic search algorithm to determine the individual PWLs of machines as well as loud machines (or vehicles), based on the parameter-setting-free harmony-search (PSF-HS) algorithm. This algorithm can be applied into determining the dominant noise sources of several vehicles in the cases of road cross sections and congested housing complex.