• International Journal of Aeronautical and Space Sciences
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• 제14권4호
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• pp.341-349
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• 2013

This paper considers the optimum design of flexbeam cross-sections for a full-scale bearingless helicopter rotor, using an efficient hybrid optimization algorithm based on particle swarm optimization, and an improved genetic algorithm, with an effective constraint handling scheme for constrained nonlinear optimization. The basic operators of the genetic algorithm, of crossover and mutation, are revisited, and a new rank-based multi-parent crossover operator is utilized. The rank-based crossover operator simultaneously enhances both the local, and the global exploration. The benchmark results demonstrate remarkable improvements, in terms of efficiency and robustness, as compared to other state-of-the-art algorithms. The developed algorithm is adopted for two baseline flexbeam section designs, and optimum cross-section configurations are obtained with less function evaluations, and less computation time.

• Industrial Engineering and Management Systems
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• 제8권1호
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• pp.14-21
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• 2009

We formulate a mathematical model of remanufacturing system as multi-stage reverse Logistics Network Problem (mrLNP) with minimizing the total costs for reverse logistics shipping cost and inventory holding cost at disassembly centers and processing centers over finite planning horizons. For solving this problem, in the 1st and the 2nd stages, we propose a Genetic Algorithm (GA) with priority-based encoding method combined with a new crossover operator called as Weight Mapping Crossover (WMX). A heuristic approach is applied in the 3rd stage where parts are transported from some processing centers to one manufacturer. Computer simulations show the effectiveness and efficiency of our approach. In numerical experiments, the results of the proposed method are better than pnGA (Prufer number-based GA).

• Journal of Communications and Networks
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• 제18권1호
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• 한국디자인학회:학술대회논문집
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• 한국디자인학회 2001년도 디자인학연구 2001 봄 학술발표회 논문집
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• pp.156-157
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• 2001

• Journal of Information Processing Systems
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• 제19권4호
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• 한국음향학회지
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• 제33권3호
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• pp.184-190
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• 2014

스피커 시스템은 가청 주파수 대역 20 ~ 20,000 Hz를 하나의 유닛으로 재생하는 것이 이상적이지만, 물리적으로 구현하기 어렵다. 따라서 두 개 또는 그 이상의 유닛을 사용하고, 멀티웨이 시스템으로 구성하여 오디오 대역을 커버한다. 멀티웨이 스피커 시스템에서는 고음과 저음의 유닛이 정상적으로 동작되도록 크로스오버 네트워크 필터를 필수적으로 사용해야 한다. 네트워크 필터의 크로스오버 주파수는 대부분 1 ~ 4 kHz 대역에 존재하며, 이 대역은 명료도의 기여율이 높고 음질에 미치는 영향이 아주 크다. 그러나 여러 가지 원인 때문에 크로스오버 주파수 대역에서 위상과 진폭 특성이 정확하게 결합되지 않은 경우가 많다. 즉, 유닛 간의 거리 차와 전기적인 특성 차이 때문에 크로스오버 주파수에서 유닛 간의 진폭과 위상 특성이 정확하게 결합되지 않아서 주파수 특성이 불규칙해지고, 그 결과 음질이 좋지 않고 명료성도 나빠진다. 크로스오버 주파수에서 유닛들을 정확하게 결합시키기 위해서는 각 유닛의 진폭 특성뿐만 아니라 위상 특성까지도 고려하여 결합시켜야 한다. 본 논문에서는 유닛 간의 지연 시간을 조정하여 크로스오버 주파수에서 평탄한 주파수 특성이 되도록 하는 방법과 유닛들의 주파수 롤 오프 특성도 고려한 필터 선택 방법을 제안하였다. 그 결과 크로스오버 주파수 대역에서 ${\pm}1$ dB의 평탄한 주파수 특성이 얻어지고 명료성도 향상되었다.

• 설비공학논문집
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• 제14권11호
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• pp.948-953
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• 2002

The electronic expansion valve (EEV) may be used to control the refrigerant flow rate for the multi-type heat pump. Stepping motor driven EEV may precisely control the refrigerant flow rate to meet each internal load requirement. To control the EEV, PI algorithm may be used. But the hysteresis of EEV deteriorates the performance of superheat control. To reduce the performance degradation, the PI algorithm along with the dither signal may be used. The dither signal, with about 10 times higher frequency than the system crossover frequency and about 10 times larger magnitude than the deadband of hysteresis, was selected for the superheat control of EEV. Experimental results showed the improvement of EEV control by adding the dither signal to the PI algorithm.

• 한국보육지원학회지
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• 제10권2호
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• pp.21-41
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• 2014

본 연구의 목적은 국악장단을 적용한 크로스오버 음악활동이 유아의 다문화 인식에 미치는 영향을 알아보기 위한 연구이다. 본 연구의 대상은 Y시에 위치한 J유치원의 만5세 1반(실험집단 21명)과 S유치원의 만5세 2반(비교집단 20명, 통제집단 20명)의 61명(남31명, 여 30명)이다. 실험집단에는 본 연구자가 개발한 국악장단을 적용한 크로스오버 음악활동을, 비교집단에는 국악중심 음악 활동을, 통제집단에는 5세 누리과정의 음악수업을 각각 20회기동안 적용하였다. 연구결과 다문화인식 하위요인 중 사후 문화개방성 점수와 사후 문화수용성 점수는 국악장단을 적용한 크로스오버 음악활동을 실시한 실험집단이 비교집단과 통제집단보다 통계적으로 유의미한 수준에서 더 높은 것으로 나타났으며, 사후 문화존중성은 국악중심 음악활동을 실시한 비교집단에서 통계적으로 유의미한 수준으로 더 높게 나타났다. 이러한 연구 결과는 국악장단을 적용한 크로스오버 음악활동은 유아의 다문화 인식의 하위요소인 문화개방성과 문화수용성의 인식 증진에 효과가 있음을 시사한다.

• 한국자동차공학회논문집
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• 제6권4호
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• pp.76-85
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• 1998

Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2574-2587
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• 2019

Blind Source Separation (BSS) is a technique used to separate supposed independent sources of signals from a given set of observations. In this paper, the High Exploration Particle Swarm Optimization (HEPSO) algorithm, which is an enhancement of the Particle Swarm Optimization (PSO) algorithm, has been used to separate a set of source signals. Compared to PSO algorithm, HEPSO algorithm depends on two additional operators. The first operator is based on the multi-crossover mechanism of the genetic algorithm while the second one relies on the bee colony mechanism. Both operators have been employed to update the velocity and the position of the particles respectively. Thus, they are used to find the optimal separating matrix. The proposed method enhances the overall efficiency of the standard PSO in terms of good exploration and performance. Based on many tests realized on speech and music signals supplied by the BSS demo, experimental results confirm the robustness and the accuracy of the introduced BSS technique.