• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.247-250
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• 2006

Integrating a GPS based vehicle navigation system and the latest optimal algorithms, this research aims to develop a real-time decision support platform for concrete plant to provide the optimal solutions for ready mixed concrete delivery. The platform includes fleet tracking system, simulation and optimization tools, and visual interface which is useful to monitor delivery progress, to obtain crucial historical and real-time data for simulation, and to improve the efficiency of the plant operation. This paper presents configuration of the system and performance evaluation based on operational data.

• Journal of information and communication convergence engineering
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• 제3권1호
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• pp.33-37
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• 2005

One of the most important feature of the Mobile Manipulator is redundant freedom. Using the redundant freedom, Mobile Manipulator can move various mode, perform dexterous motion. In this paper, to improve robot job ability, as two robots perform a job in co-operation control, we studied optimal position and posture of Mobile Manipulator with minimum movement of each robot joint. Kinematics of mobile robot and task robot is solved. Using mobility of Mobile robot, weight vector of robots is determined. Using Gradient methode, global motion trajectory is minimized. so the job which Mobile Manipulator perform is optimized. The proposed algorithm is verified with PURL-II which is Mobile Manipulator combined Mobile robot and task robot. and discussed the result.

• 한국태양에너지학회 논문집
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• 제31권2호
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• pp.143-147
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• 2011

On-off differential controller is one of the very important component which has influence on the system performance of the solar hot water system. In this study, it was analysed the influence of "on-off" setting temperature on the system efficiency and the electrical consumption by circulation pump. This study was performed by computer simulation using TRNSYS program. The simulation system was developed in this study was verified the its reliability by the experimental results.

• 상하수도학회지
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• 제31권6호
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• pp.587-597
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• 2017

This study aimed to develop a method to optimize residual chlorine concentrations in the process of providing water supply. To this end, this study developed a model capable of optimizing the chlorine input into the clearwell in the purification plant and the optimal installation location of rechlorination facilities, and chlorine input. This study applied genetic algorithms finding the optimal point with appropriate residual chlorine concentrations and deriving a cost-optimal solution. The developed model was applied to SN purification plant supply area. As a result, it was possible to meet the target residual chlorine concentration with the minimum cost. Also, the optimal operation method in target area according to the water temperature and volume of supply was suggested. On the basis of the results, this study derived the most economical operational method of coping with water pollution in the process of providing water supply and satisfying the service level required by consumers in the aspects of cost effectiveness. It is considered possible to appropriately respond to increasing service level required by consumers in the future and to use the study results to establish an operational management plan in a short-term perspective.

• 한국지열·수열에너지학회논문집
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• 제6권2호
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• pp.1-7
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• 2010

The objective of this study is to find the optimal control algorithm of a hybrid Plant, which is combined by renewable energy plant of the GSHP(Geothermal Source Heat Pump) and the normal plant (Chiller, boiler). The work presented in this study was carried out in the EnergyPlus(Version 2.0). The EnergyPlus was modified in order to simulate the hybrid plant. The plant system was controlled by the load-range-based operation in which schemes select a user specified set of equipment for each user specified range of a particular simulation condition. In the use of the load-range-based operation, four kind of control cases were defined and simulated in order to obtain the optimal control algorithm of the hybrid plant. The result showed that the Case 2 was the optimal control algorithm which used the GSHP as a base operating plant and the normal plant as an assistant operating plant. Even though the normal plant was operated in full load and the renewable energy plant of the GSHP was operated in partial load, the annual energy consumption of the normal plant was larger than that of the GSHP plant.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• 품질경영학회지
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• 제18권2호
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• pp.18-24
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• 1990

The location of inspection stations is a significant component of production systems. In this paper, a prototype expert system is designed for deciding the optimal location of inspection stations. The production system is defined as a single channel of n serial operation stations. The potential inspection station can be located after any of the operation stations. Nonconforming units are generated from a compound binomial distribution with known parameters at any given operation station. Traditionally Dynamic programming, Zero-one integer programming, or Non-linear programming techniques are used to solve this problem. However a problem with these techniques is that the computation time becomes prohibitively large when t be number of potential inspection stations are fifteen or more. An expert system has the potential to solve this problem using a rule-based system to determine the near optimal location of inspection stations. This prototype expert system is divided into a static database, a dynamic database and a knowledge base. Based on defined production systems, the sophisticated rules are generated by the simulator as a part of the knowledge base. A generate-and-test inference mechanism is utilized to search the solution space by applying appropriate symbolic and quantitative rules based on input data. The goal of the system is to determine the location of inspection stations while minimizing total cost.

• 물과 미래
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• 제28권6호
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• pp.217-228
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• 1995

홍수기중 최적의 저수지운영을 위해 서로 상반되는 이수와 치수를 조화시키기 위한 전반적이고 체계적인 운영방안을 제안하였다. 본 연구는 비홍수기의 용수수요 보장을 고려히 홍수기중 저수지의 제한수위를 결정하기 위한 것이다. 단기간별요 가변제한수위(VRWL)와 최소 확보저수위 (MRWL)를 적용하여 저수용량의 재할당으로 최적 운영방안이 유도되었다. 또한 갈수빈도해석에 따른 저수지운영분석으로 비홍수기의 용수공급을 위해 확보되어야 할 홍수기말 저수지의 수위조건에 관하여 대청과 충주 다목적댐을 대상으로 적용하고 그 결과를 분석하였다.

• 산업공학
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• 제24권3호
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• pp.220-230
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• 2011

The multi-reservoir operation problem for efficient utilization of water resources involves conflicting objectives, and the problem can be solved by varying weight coefficient on objective functions. Accordingly, decision makers need to choose appropriate weight coefficients balancing the trade-offs among multiple objectives. Although the appropriateness of the weight coefficients may depend on the total amount of water inflow, reservoir operating policy may not be changed to a certain degree for different hydrological conditions on inflow. Therefore, we propose to use fuzzy Data Envelopment Analysis (DEA) to rank the weight coefficients in consideration of the inflow variation. In this approach, we generate a set of Paretooptimal solutions by applying different weight coefficients on Coordinated Multi-reservoir Operating Model. Then, we rank the Pareto-optimal solutions or the corresponding weight coefficients by using Fuzzy DEA model. With the proposed approach, we can suggest the best weight coefficients that can produce the appropriate Pareto-optimal solution considering the uncertainty of inflow, whereas the general DEA model cannot pinpoint the best weight coefficients.

• 조명전기설비학회논문지
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• 제12권2호
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• pp.69-76
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• 1998

본 논문에서는 배압터빈과 추기복수터빈으로 이루어진 열병합 발전플랜트의 최전운전을 결정할 수 있는 새로운 알고리즘을 제시한다. 제시한 알고리즘은 플랜트가 운전중에 직접 온 라인으로 취할 수 있는 증가량만을 파라메타로 하여 보일러와 터빈-발전기의 최적부하를 결정할 수 있다. 본 알고리즘은 비선형 경비함수와 해당 제한사항들로 이루어져 있으며 실제 운전중인 열병합 발전플랜트와 비교 시뮬레이션을 실시한 결과 만족할만한 결과를 얻었다. 즉 실제 운전 데이터와 비교해본 결과 공정의 증기 부하량에 따라 1.2∼4.5[%]의 운전경비 절감효과를 얻을 수 있었다. 또한 본 알고리즘은 필요한 입력 데이터를 공정으로부터 쉽게 온 라인으로 취할 수 있어 프로세스 컴퓨터로 용이하게 구현할 수 있다.