• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2000년도 추계학술대회논문집
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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.

• 전기학회논문지
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• 제66권12호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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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.

• 한국통신학회논문지
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• 제32권4A호
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• pp.358-364
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• 2007

RFID(Radio Frequency IDentification) 기술은 라디오 주파수를 사용하는 비접촉 자동인식 기술이다. 이런 RFID 기술의 확산을 위해서는 리더(reader)가 다수의 태그(tag)를 짧은 시간 안에 인식하는 다중 태그 식별 문제를 해결 해야만 한다. 지금까지 이 문제를 해결하기 위한 충돌 방지(anti-collision) 알고리즘이 많이 개발되었고 이것들은 크게 알로하(ALOHA) 기반 알고리즘과 트리(tree) 기반 알고리즘으로 나뉜다. 본 논문에서는 이 두 가지 방법의 특징을 혼합한 새로운 충돌 방지 알고리즘 2가지를 제안한다. 그리고 대표적인 충돌 방지 알고리즘인 18000-6 Type A, Type B, Type C, query tree 알고리즘과 성능 비교 및 평가를 한다.

• International Journal of Computer Science & Network Security
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• 제21권9호
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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.

• 한국전자거래학회지
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• 제20권1호
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• pp.79-88
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• 2015

웹 서버나 데이터베이스 서버와 같은 컴퓨터 서버들은 연속적으로 리퀘스트 스트림을 받는다. 이런 서버들은 유저들에게 최선의 서비스를 제공하기 위해 리퀘스트들을 스케줄링하여야 한다. 이 논문은 분할 가능 리퀘스트들을 스케줄링할 때 총 스트레치를 최소화하기 위해 혼합 유전자 알고리즘을 제안한다. 리퀘스트의 스트레치는 리퀘스트가 시스템에 머무는 시간에 대한 반응 시간의 비율로 정의된다. 혼합 유전자 알고리즘은 유전자 알고리즘의 활용과 탐구 능력를 개선하기 위해 시드 선택과 개발의 아이디어를 도입하였다. 혼합 유전자 알고리즘과 유전자 알고리즘의 성능을 비교하기 위하여 광범한 컴퓨터 실험이 실행되었다.

• 전자공학회논문지B
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• 제30B권10호
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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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• 제6권4호
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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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• 제10권1호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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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.