• 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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.947-951
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• 2005

The concept of group technology has been successfully applied to many production systems including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem which has been intensively studied over 40 years. We obtain a production schedule of several family products on a single facility where setup times and costs can be reduced by using the concept of group technology. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem (GT-ELSP). Numerical example shows that the developed heuristic and the hybrid genetic algorithm outperform the existing heuristics.

• 경영과학
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• 제17권1호
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• pp.135-144
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• 2000

This paper describes a scheduling problem of the panel block assembly shop in a shipbuilding industry. Because the shipbuilding is a labor intensive industry the most important consideration in a panel block assembly shop is the workload balancing. which balances man-hour weight and welding length and so on. It should be determined assembly schedule and workstation considering a daily load balancing and a workstation load balancing simultaneously. To solve the problem we develop a hybrid genetic algorithm. Hybrid genetic algorithm proposed in this paper consists of two phases. The first phase uses the heuristic method to find a initial feasible solution which provides a useful information about optimal solution. The second phase proposes the genetic algorithm to derive the optimal solution with the initial population consisting of feasible solutions based on the initial solution. Finally we carried out computational experiments for this load balancing problem which indicate that developed method is effective for finding good solutions.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1086-1091
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• 2005

This paper focuses on intelligent control of induction motor by hybrid system consisting of GA-PSO. Induction motor has been using in industrial area. However, it is challengeable on how we control effectively. From this point, an optimal solution using GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is introduced to intelligent control. In this case, it is possible to obtain local solution because chromosomes or individuals which have only a close affinity can convergent. To improve an optimal learning solution of control, This paper deal with applying PSO and Euclidian data distance to mutation procedure on GA's differentiation. Through this approaches, we can have global and local optimal solution together, and the faster and the exact optimal solution without any local solution. Four test functions are used for proof of this suggested algorithm.

• 경영과학
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• 제30권2호
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• pp.31-42
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• 2013

The vehicle routing problem (VRP) can be described as a problem to find the optimum traveling routes from one or several depot (s) to number of geographically scattered customers. This study executes a revised Heterogeneous Vehicle Routing Problem (HVRP) to minimize the cost that needs to conduct efficiently the snow removal operations of Air Wing under available resources and limited operations time. For this HVRP, we model the algorithm of an hybrid Ant Colony System (ACS). In the initial step for finding a solution, the modeled algorithm applies various alterations of a parameter that presents an amount of pheromone coming out from ants. This improvement of the initial solution illustrates to affect to derive better result ultimately. The purpose of this study proves that the algorithm using Hybrid heuristic incorporated in tabu and ACS develops the early studies to search best solution.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.215-220
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• 1998

In order to optimize fuzzy model, we use the optimal algorithm with a hybrid type in the identification of premise parameters and standard least square method in the identification of consequence parameters of a fuzzy model. The hybrid optimal identification algorithm is carried out using a genetic algorithm and improved complex method. Also, the performance index with weighting factor is proposed to achieve a balance between the insults of performance for the training and testing data. Several numerical examples are used to evaluate the performance of the proposed model.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.215-219
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• 1998

This paper presents a practical application of fuzzy logic control to temperature control of glass melting furnace. Due to the characteristics of glass melting furnace, a hybrid algorithm of conventional PI controller and fuzzy logic controller is proposed and discussed. Practical implementation results of the production furnace showed the effectiveness of the proposed control algorithm.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 추계학술대회 논문집
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• pp.473-474
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• 2010

• 한국정보과학회논문지:시스템및이론
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• 제26권11호
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• pp.1382-1390
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• 1999

본 논문에서는 ATM 망에서 대표적 사용 파라미터 제어(UPC) 알고리즘인 리키버켓 알고리즘과 윈도우 알고리즘의 하나인 EWMA 알고리즘을 결합한 복합형 UPC 알고리즘을 제안하고 그 성능을 평가 분석하였다.제안된 알고리즘은 최대전송율을 제어하는 리키버켓과 평균전송율을 제어하는 EWMA를 병렬로 결합하여, 최대전송율과 평균전송율을 동시에 고려하였다. ON/OFF 트래픽 소스 모델을 적용, BONeS를 이용하여 모의실험한 결과 제안 알고리즘이 기존의 리키버켓 알고리즘에 비해 셀 손실율과 버퍼 크기면에서 우수한 성능을 나타냈다.Abstract In this paper, a hybrid UPC algorithm is proposed, which combines the representative Leaky Bucket UPC algorithm with the EWMA window algorithm in the ATM network and then its performance is evaluated. The hybrid UPC algorithm is made up of Leaky Bucket and EWMA, which control the peak bit rate and the mean bit rate, respectively. According to the result of the simulation using BONeS with the On/Off traffic source model, it is revealed that the proposed UPC algorithm has superior performance to the existing Leaky Bucket UPC algorithm with regard to both the cell loss rate and the buffer size.

• 산업공학
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• 제23권2호
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• pp.147-155
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• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.