• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.131-142
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• 2000

Facility layout is the early stage of system design that requires a mid-term or long-term plan. Since improper facility layout might incur substantial logistics cost including material handling and re-installment costs, due consideration must be given to decisions on facility layout. Facility layout is concerned with low to arrange equipment necessary for production in a given space. Its objective is to minimize the sum of all the products of each equipment's amount of flow multiplied by distance. Facility layout also is related to the issue of NP-complete, i.e., calculated amounts exponentially increase with the increase of the number of equipment. This study discusses Hybrid GA developed, as an algorithm for facility layout, to solve the above-mentioned problems. The algorithm, which is designed to efficiently place equipment, automatically produces a horizontal passageway by the block, if a designer provides the width and length of the space to be handled. In addition, this study demonstrates the validity of the Algorithm by comparing with existing algorithms that have been developed. We present a Hybrid GA approach to the facility layout problem that improves on existing work in terms of solution quality and method. Experimental results show that the proposed algorithm is able to produce better solution quality and more practical layouts than the ones obtained by applying existing algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1782-1791
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• 2017

In this paper, an optimal design of hybrid magnetic levitation(Maglev) system using intelligent optimization algorithms is proposed. The proposed maglev system adopts hybrid suspension system with permanent-magnet(PM) and electro magnet(EM) to reduce the suspension power loss and the teaching-learning based optimization(TLBO) that can overcome the drawbacks of conventional intelligent optimization algorithm is used. To obtain the mathematical model of hybrid suspension system, the magnetic equivalent circuit including leakage fluxes are used. Also, design restrictions such as cross section areas of PM and EM, the maximum length of PM, magnetic force are considered to choose the optimal parameters by intelligent optimization algorithm. To meet desired suspension power and lower power loss, the multi object function is proposed. To verify the proposed object function and intelligent optimization algorithms, we analyze the performance using the mean value and standard error of 10 simulation results. The simulation results show that the proposed method is more effective than conventional optimization methods.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.120-122
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• 2006

The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. Thestructural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4A
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• pp.358-364
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• 2007

RFID, Radio Frequency Identification, technology is a contactless automatic identification technology using radio frequency. For this RFID technology to be widely spread, the problem of multiple tag identification, which a reader identifies a multiple number of tags in a very short time, has to be solved. Up to the present, many anti-collision algorithms have been developed in order to solve this problem, and those can be largely divided into ALOHA based algorithm and tree based algorithm. In this paper, two new anti-collision algorithms combining the characteristics of these two categories are presented. And the performances of the two algorithms are compared and evaluated in comparison with those of typical anti-collision algorithms: 18000-6 Type A, Type B, Type C, and query tree algorithm.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.41-50
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• 2021

Cloud computing is one of the most expanding technologies nowadays; it offers many benefits that make it more cost-effective and more reliable in the business. This paper highlights the various benefits of cloud computing and discusses different cryptography algorithms being used to secure communications in cloud computing environments. Moreover, this thesis aims to propose some improvements to enhance the security and safety of cloud computing technologies.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.79-88
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• 2015

Many servers, such as web and database servers, receive a continual stream of requests. The servers should schedule these requests to provide the best services to users. In this paper, a hybrid genetic algorithm is proposed for scheduling divisible requests without interruption in which the objective is to minimize the total stretch. The stretch of a request is the ratio of the amount of time the request spent in the system to its response time. The hybrid genetic algorithm adopts the idea of seed selection and development in order to improve the exploitation and exploration power of genetic algorithms. Extensive computational experiments have been conducted to compare the performance of the hybrid genetic algorithm with that of genetic algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.1-12
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• 1993

A multiprocessor system for high-speed processing of hybrid image coding algorithms such as H.261, MPEG, or Digital HDTV is presented in this study. Using a combination of highly parallel 32-bit microprocessor, DCT(Discrete Cosine Transform), and motion detection processor, a new processing module is designed for the implementation of high performance coding system. The sysyem is implemented to allow parallel processing since a single module alone cannot perform hybrid coding algorithms at high speed, and crossbar switch is used to realize various parallel processing architectures by altering interconnections between processing modules within the system.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.429-436
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• 2005

In this paper, operation algorithms are evaluated for a fuel cell hybrid electric vehicle (FCHEV). Power assist, load leveling and equivalent fuel algorithm are proposed and implemented in the FCHEV performance simulator. It is found from the simulation results that the load leveling algorithm shows poor fuel economy due to the system charge and discharge efficiency. In the power assist and equivalent fuel algorithm, the fuel cell stack is operated in a relatively better efficiency region owing to the battery power assist, which provides the improved fuel economy.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.24-33
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• 2011

In this paper, we consider the Location-Routing Problem with simultaneous pickup and delivery (LRPSPD) which is a general case of the location-routing problem. The LRPSPD is defined as finding locations of the depots and designing vehicle routes in such a way that pickup and delivery demands of each customer must be performed with same vehicle and the overall cost is minimized. Since the LRPSPD is an NP-hard problem, we propose a hybrid heuristic approach based on genetic algorithms (GA) and simulated annealing (SA) to solve the problem. To evaluate the performance of the proposed approach, we conduct an experimental study and compare its results with those obtained by a branch-and-cut algorithm on a set of instances derived from the literature. Computational results indicate that the proposed hybrid algorithm is able to find optimal or very good quality solutions in a reasonable computation time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.