• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5622-5632
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• 2011

This paper presents the simulation design and analysis of Integrated Logistics System(ILS) which is operated by using the AGV(Automated Guided Vehicle). To maximize the operation performances of ILS with AGV, many parameters should be considered such as the number, velocity, and dispatching rule of AGV, part types, scheduling, and buffer sizes. We established the design of experiment in a way of Orthogonal Array in order to consider (1)maximizing the throughput; (2)maximizing the vehicle utilization; (3)minimizing the congestion; and (4)maximizing the Automated Storage and Retrieval System(AS/RS) utilization among various critical factors. Furthermore, we performed the optimization by using the simulation-based analysis and Evolution Strategy(ES). As a result, Orthogonal Array which is conducted far fewer than ES significantly saved not only the time but the same outcome when compared after validation test on the result from the two methods. Therefore, this approach ensures the confidence and provides better process for quick analysis by specifying exact experiment outcome even though it provides small number of experiment.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.13-18
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• 2000

In this paper, an Adaptive Evolutionary Computation(AEC) is proposed. AEC uses a genetic algorithm(GA) and an evolution strategy (ES) in an adaptive manner is order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. AEC is used to design the membership functions and the scaling factors of fuzzy logic controller (FLC). To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC series motor system with nonlinear characteristics. Experimental results show that the proposed controller has better performance than that of PD controller.

• Journal of Mechanical Science and Technology
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• v.17 no.2
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• pp.187-196
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• 2003

In this paper, a new methodology of evolutionary computations - An Adaptive Evolutionary Algorithm (AEA) is proposed. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations : global search capability of GA and local search capability of ES. In the reproduction procedure, the proportions of the population by GA and ES are adaptively modulated according to the fitness. AEA is used to. designing fuzzy logic controller (FLC) for a high-angle-of-attack flight system for a super-maneuverable version of F-18 aircraft. AEA is used to determine the membership functions and scaling factors of an FLC. The computer simulation results show that the FLC has met both robustness and performance requirements.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.632-637
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• 2008

In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Structural Engineering and Mechanics
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• v.44 no.3
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• pp.379-403
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• 2012

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

• KIEE International Transactions on Power Engineering
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• v.5A no.3
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• pp.269-279
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• 2005

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to find the optimal switch position because of its numerous local minima. In this investigation, a parallel AEA was developed for the reconfiguration of the distribution system. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of GA and the local search capability of ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC-cluster system consisting of 8 PCs·was developed. Each PC employs the 2 GHz Pentium IV CPU, and is connected with others through switch based fast Ethernet. The new developed algorithm has been tested and is compared to distribution systems in the reference paper to verify the usefulness of the proposed method. From the simulation results, it is found that the proposed algorithm is efficient and robust for distribution system reconfiguration in terms of the solution quality, speedup, efficiency, and computation time.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.3
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• pp.81-85
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• 2001

Processes for optimizing the coil shape of deflection yoke are proposed A very accurate and practical winding modeler is developed and volume integral equation method (VIEM) is used for field calculation. Two steps of optimizations are done by using (1+1) evolution strategy. Those are dimensional optimization and pin-position optimization Various techniques are applied for reducing computational time for the optimization.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.1
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• pp.90-94
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• 2005

As the structure of the piezoelectric bimorph cantilever becomes increasingly more complicated, a more accurate and efficient analysis of piezoelectric media is needed. In this paper, the piezoelectric transducer is analyzed by using the three-dimensional finite element method. The validity of the three-dimensional finite element routine is confirmed by comparing the experimental result. The resonance characteristics, such as resonance frequency and anti-resonance frequency, of the piezoelectric cantilever are calculated by the experimentally verified three dimensional finite element method. Subsequently, the characteristics, such as mechanical displacement and impedance, are calculated at the resonance frequency. Besides, to design the piezoelectric bimorph cantilever shape that maximizes displacement at the tip, the ES (Evolution Strategy) algorithm is applied. Finally, optimal design for the fan of the piezoelectric cantilever is fulfilled to obtain maximum displacement at the tip. From these results, the application potentiality of the piezoelectric bimorph cantilever fan is identified.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.153-158
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• 1998

In this paper, we present a design of optimal 2-DOF PID controller for control of gantry crane which has to control swing motion and trolley position. For tuning the parameter of 2-DOF PID controller, we used evolution strategy(ES). During operate the crane system in yard, the goal is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. However, we developed an optimal controller which has to control the crane system with disturbance.