• Clean Technology
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• v.7 no.4
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• pp.265-272
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• 2001

본 연구는 지구 온난화 현상의 주원인이 되는 $CO_2$ 를 화력발전소 연도가스로부터 분리 회수하기 위한 PSA 공정 개발용 기초자료를 습득하기 위하여 실시하였다. 연도가스와 유사한 조건하에서 국내에서 제조된 활성탄을 이용하여 이산화탄소 및 밸런스를 이루고 있는 질소 가스의 흡착평형 및 흡착속도 실험을 실시하였으며, 분석을 위하여 자체 제작한 장치(부피측정법) 및 TGA 장치를 각각 사용하였다. 이 연구에서 획득한 흡착등온선으로부터 사용된 흡착제가 이산화탄소의 분리에 적절한지 판단할 수 있었다. 또한, TGA에 의해 측정된 흡착속도 자료는 향후 사용될 흡착탑의 파과곡선 예측에 사용될 수 있다. 연구결과로부터 다음과 같은 사실을 알 수 있었다. 첫째, 낮은 흡착온도 일수록 흡착량이 많고 빠른 흡착속도를 나타내었다. 둘째, 압력이 높아질수록 흡착량은 증가하였다. 셋째, SGT활성탄이 SGA-100 및 SGP-100활성탄 보다 다소 많은 흡착량과 빠른 흡착속도를 보였다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.1
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• pp.115-125
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• 1999

Simple Genetic Algorithm(SGA) proposed by J. H. Holland is a population-based optimization method based on the principle of the Darwinian natural selection. The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. Although GA does well in many applications as an optimization method, still it does not guarantee the convergence to a global optimum in some problems. In designing intelligent systems, specially, since there is no deterministic solution, a heuristic trial-and error procedure is usually used to determine the systems' parameters. As an alternative scheme, therefore, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve. In this paper we review the existing co-evolutionary algorithms and propose co-evolutionary schemes designing intelligent systems according to the relation between the system's components.

• Journal of the Korean Geotechnical Society
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• v.16 no.3
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• pp.47-55
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• 2000

본 연구에서는, 유전자 알고리즘을 이용한 piled raft 기초의 최적설계 기법을 제시하였다. 최적설계에 사용한 목적함수는 구조물의 사용한계에 해당하는 부등침하량과 piled raft 기초의 시고비용 차원에서의 말뚝과 raft의 총 중량으로 하였다. 유전자 알고리즘은 다읜의 적자생존의 법칙을 따르는 자연진화 법칙을 바탕으로 한 최적화 기법이다. 본 연구에서는 piled raft 기초의 해석방법으로 Clancy(1993)가 제시한 "hybrid" 해석방법을 사용하였으며, 유전자 알고리즘기법은 Goldberg(1989)가 제시한 단순 유전자 알고리즘(SGA)을 적용하였다. 또한 유전자 알고리즘을 이용한 최적설계기법의 유효성을 평가하기 위해 설계예제 및 매개변수변화연구를 통해 piled raft 기초시스템의 중요 설계인자들에 대한 분석을 수행하였다. 매개변수변화연구로부터 말뚝의 길이와 raft의 두께가 증가할수록 piled raft 기초시스템의 전체 중량은 일정한 값에 점차적으로 수렴하였으며, 지반의 강정, raft의 두께 말뚝의 길이 및 강성이 증가할수록 말뚝의 최적위치는 raft의 중앙에 집중되는 경향으로 나타났다.경향으로 나타났다.

• Proceedings of the Korean Professional Engineer Association Conference
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• 1984.12a
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• pp.77-82
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• 1984

The small group activities (SGA) was introduced into some of enterprises in Korea in 1967 and plant division, Saemaul undong Headquarters had encouraged Quality Control Circles (QCC) within the manufacturing corporations in assistance of central government. Registered small groups as of august 31, 1984 amounted up to 78,243 units and the number of members were 791,512. Meanwhile, small and medium industries have mostly introduced small group activities considerably later and less actively managed than large business. Main reasons for the less effectiveness of the activities are due to lack of management skills and less awareness of it from management and workers group. Effective small group activities are presumed to be successful only with labor management cooperation on the basis of human-oriented management philosophy. The small group activities are also prevalent in service sector. More derivative methods have been developed and more members are willingly participating in training programs. The small group which is basically a horizontal organization unit, promotes communication within the whole organization. In consideration of the social circumstances and traditions, the flexible model of the small group activities suitable to the corporate environment, will contribute to industrial development.

• Korean Management Science Review
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• v.20 no.1
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• pp.51-64
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• 2003

The JSSP (Job Shop Scheduling Problem) Is one of the most general and difficult of all traditional scheduling problems. The goal of this research is to develop an efficient scheduling method based on genetic algorithm to address JSSP. we design scheduling method based on SGA (Single Genetic Algorithm) and PGA (Parallel Genetic Algorithm). In the scheduling method, the representation, which encodes the job number, is made to be always feasible, initial population is generated through integrating representation and G&T algorithm, the new genetic operators and selection method are designed to better transmit the temporal relationships in the chromosome, and island model PGA are proposed. The scheduling method based on genetic algorithm are tested on five standard benchmark JSSPs. The results were compared with other proposed approaches. Compared to traditional genetic algorithm, the proposed approach yields significant improvement at a solution. The superior results indicate the successful Incorporation of generating method of initial population into the genetic operators.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.63-66
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• 2001

Recently, as the demand for high efficiency, multi function machine tools is increasing, domestic machine tool industries are investing in research and development for precision machine tools with high speed. This trend is closely correlated with the design technique which is necessary to make new type machine tool compatible with new production system. To achieve high precision, high speed machine tools with reduced chatter, it is needed to develop dynamically rigid structure. In this paper, dynamic optimization of machine structure is presented. At this procedure of dynamic design, dynamic compliance is minimized using Simple Genetic Algorithm(SGA)

• Journal of the Korea Society for Simulation
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• v.9 no.1
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• pp.93-108
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• 2000

The stochastic manufacturing system has one or more random variables as inputs that lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of the system. These estimates could greatly differ from the corresponding real characteristics for the system. Multiple replications are necessary to get reliable information on the system and output data should be analyzed to get optimal solution. It requires too much computation time practically, In this paper a GA method, named Stochastic Genetic Algorithm(SGA) is proposed and tested to find the optimal solution fast and efficiently by reducing the number of replications.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.313-316
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• 2008

에어컨 시스템은 압축기(Compressor), 응축기(Condenser), 증발기(Evaporator)와 확장밸브(Expansion Valve)로 구성되며, 에어컨 시스템에서 과열도와 저압(증발기의 압력)은 시스템의 효율 증대 및 성능 개선과 안정성에 대하여 결정적인 영향을 미친다. 따라서, 과열도와 저압을 조절하기 위해, 각각의 압축기내의 인버터 주파수와 확장밸브의 개도 제어가 중요하며 선형과 비선형 시스템 모두에 대하여 견실한 성능을 나타내고, 외란에 대하여 강인한 성능을 보이는 퍼지 제어기를 설계한다. 본 논문에서는 과열도와 저압을 제어하기 위하여, 3대의 확장밸브와 1대의 압축기를 가진 에어컨 시스템에 대하여 다중 퍼지 제어기를 설계한다. 또한, 각 제어 플랜트에 대하여 최적의 퍼지 제어기를 설계하기 위하여 3가지 최적화 알고리즘을 사용한다. 즉, 직렬 유전자 알고리즘(Serial Genetic Algorithm; SGA)과 병렬 유전자 알고리즘인 계층적 공정 경쟁 유전자 알고리즘(Hierarchical Fair Competition Genetic Algorithm; HFCGA), 그리고 Particle Swarm Optimization(PSO)을 사용하여 다중 퍼지 제어기를 최적화하고 시뮬레이션의 결과를 비교한다.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.20
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• pp.83-112
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• 2003

This study primarily concerns the Sale and Supply of Goods to Consumers Regulations 2002, focusing on the newly amended rules of the Sale of Goods Act(1979). It describes and analyzes the provisions of Regulations 2002 in a comparative way in order to provide legal advice to the sellers who plans to enter into English consumer markets. It also attempts to compare the rules of Regulations 2002 with those of CISG and to evaluate them in light of the discipline of Law and Economics the basic question of which is whether a solution from one jurisdiction may enhence 'efficiency', serving the goal of reducing negotiation costs through providing a set of default terms, and through imposing an efficient solution which may assist value maximizing exchange where disputes arise.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.97-109
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• 2002

Manufacturing environments in the real world are subject to many sources of change and uncertainty, such as new job releases, job cancellations, a chance in the processing time or start time of some operation. Thus, the realistic scheduling method should Properly reflect these dynamic environment. Based on the release times of jobs, JSSP (Job Shoe Scheduling Problem) can be classified as static and dynamic scheduling problem. In this research, we mainly consider the dynamic JSSP with continually arriving jobs. The goal of this research is to develop an efficient scheduling method based on GA (Genetic Algorithm) to address dynamic JSSP. we designed scheduling method based on SGA (Sing1e Genetic Algorithm) and PGA (Parallel Genetic Algorithm) The scheduling method based on GA is extended to address dynamic JSSP. Then, This algorithms are tested for scheduling and rescheduling in dynamic JSSP. The results is compared with dispatching rule. In comparison to dispatching rule, the GA approach produces better scheduling performance.