• 한국전산구조공학회논문집
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• 제23권5호
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• pp.475-482
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• 2010

본 논문에서는 대규모 자유도 시스템의 병렬처리를 위하여 2단계로 이루어진 영역분할법(Domain Decomposition Method) 기반의 병렬 알고리즘을 제안하였다. 분할된 영역의 내부 및 외부 경계를 상위영역문제로 정의하고 국부영역문제는 변위 경계조건이 모두 주어지는 분할영역에서의 Dirichlet 문제로 구성한다. 상위영역에서는 전체 상위영역에 대한 강성 행렬의 어셈블이 필요없는 반복법을 통하여 변위를 구하고, 이를 바탕으로 국부영역에서 Multi-Frontal Sparse Solver (MFSS)를 이용하여 변위를 계산한다. 상위영역문제의 연산에서 프로세서 간의 데이터 교환을 최소화하여 계산효율을 유지하며, 동시에 해석 가능한 자유도를 증대시키는 병렬 PCG(Preconditioned Conjugate Gradient)법 기반의 알고리즘을 개발하였다. 제안된 알고리즘을 적용하여 수치해석을 수행한 결과, 프로세서 수가 증가할수록 계산성능의 손실없이 해석 가능한 자유도가 비례하여 증가하는 선형 확장성을 관찰할 수 있었으며, 대규모 자유도 문제에 효과적으로 사용 가능함을 확인하였다.

• 항공우주시스템공학회지
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• 제11권1호
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• pp.41-46
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• 2017

소형 다중로터 드론의 동작 실험을 위하여 개발한 장치를 소개한다. 개발한 장치는, 볼 부슁 메카니즘, 이동형 지지대, 그리고 회전판을 적용하여 6자유도 운동이 가능하다. 병렬 처리가 가능한 FPGA기반의 제어기를 사용하여, 가속도와 자이로 센서로 부터 자세를 측정하고 모터 속도를 제어하였다. 다양한 동작을 수행하면서 실험 장치와 제어기의 동작성을 확인하였다. 결론적으로, 개발한 6자유도 실험 장치는 소형 드론 제어를 위한 제어기의 성능 검증을 위해 적합하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1100-1122
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• 2023

Scheduling user-submitted cloud tasks to the appropriate virtual machine (VM) in cloud computing is critical for cloud providers. However, as the demand for cloud resources from user tasks continues to grow, current evolutionary algorithms (EAs) cannot satisfy the optimal solution of large-scale cloud task scheduling problems. In this paper, we first construct a large- scale multi-objective cloud task problem considering the time and cost functions. Second, a multi-objective optimization algorithm based on multi-factor optimization (MFO) is proposed to solve the established problem. This algorithm solves by decomposing the large-scale optimization problem into multiple optimization subproblems. This reduces the computational burden of the algorithm. Later, the introduction of the MFO strategy provides the algorithm with a parallel evolutionary paradigm for multiple subpopulations of implicit knowledge transfer. Finally, simulation experiments and comparisons are performed on a large-scale task scheduling test set on the CloudSim platform. Experimental results show that our algorithm can obtain the best scheduling solution while maintaining good results of the objective function compared with other optimization algorithms.

• ETRI Journal
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• 제32권1호
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• pp.73-83
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• 2010

Combinatorial testing has been an active research area in recent years. One challenge in this area is dealing with the combinatorial explosion problem, which typically requires a very expensive computational process to find a good test set that covers all the combinations for a given interaction strength (t). Parallelization can be an effective approach to manage this computational cost, that is, by taking advantage of the recent advancement of multicore architectures. In line with such alluring prospects, this paper presents a new deterministic strategy, called multicore modified input parameter order (MC-MIPOG) based on an earlier strategy, input parameter order generalized (IPOG). Unlike its predecessor strategy, MC-MIPOG adopts a novel approach by removing control and data dependency to permit the harnessing of multicore systems. Experiments are undertaken to demonstrate speedup gain and to compare the proposed strategy with other strategies, including IPOG. The overall results demonstrate that MC-MIPOG outperforms most existing strategies (IPOG, IPOF, IPOF2, IPOG-D, ITCH, TConfig, Jenny, and TVG) in terms of test size within acceptable execution time. Unlike most strategies, MC-MIPOG is also capable of supporting high interaction strengths of t > 6.

• 대한산업공학회지
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• 제35권4호
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• pp.257-265
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• 2009

This paper considers the hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. In hybrid flow shops, each job is processed through multiple production stages in series, each of which has multiple identical parallel machines. The problem is to determine the allocation of jobs to the parallel machines at each stage as well as the sequence of the jobs assigned to each machine. Due to the complexity of the problem, we suggest search heuristics, tabu search and simulated annealing algorithms with a new method to generate neighborhood solutions. In particular, to evaluate and select neighborhood solutions, three surrogate objectives are additionally suggested because not much difference in the number of tardy jobs can be found among the neighborhoods. To test the performances of the surrogate objective based search heuristics, computational experiments were performed on a number of test instances and the results show that the surrogate objective based search heuristics were better than the original ones. Also, they gave the optimal solutions for most small-size test instances.

• 제어로봇시스템학회논문지
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• 제18권9호
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• pp.823-829
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• 2012

An excitation table is commonly used for vibration and ride tests for parts or assemblies of automobiles, aircrafts, or other heavy systems. The authors have analyzed several kinematic properties of an excitation table that is under development for heavy transport vehicles. It consists of one table and 7 linear hydraulic actuators. The authors have performed mobility analysis, inverse kinematics, forward kinematics, and singularity analysis. Especially, we have proposed a fast forward kinematic solution considering the limited motion of the excitation table. On the assumption that the motion variables such as rotation angles and displacements are small, the forward kinematic problem is converted to the observer problem of a linear system. This provides a fast solution. Also we have verified that there are no singularity points in the working range by numerical analysis.

• Nuclear Engineering and Technology
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• 제52권11호
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• pp.2630-2637
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• 2020

The structure design of divertor Multi-Functional Maintenance Platform (MFMP) actuated by hydraulic system for China Fusion Engineering Test Reactor (CFETR) was introduced in this paper. The model of MFMP was established according to maintenance requirements. In this paper, Newton-Euler method and the improved virtual work principle were used, the equivalent driving force of each actuator was obtained through the equivalent Jacobian inverse matrix derived from velocity relationship among the components. The accuracy of the model was verified by ADAMS simulation. The stability control of the heavy-duty components driven by hydraulic cylinders based on Newton-Euler method and improved virtual work principle was established.

• 대한전기학회논문지
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• 제45권3호
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• pp.444-450
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• 1996

A digital hardware architecture for artificial neural network with learning capability is described in this paper. It is a modified hardware architecture known as HANNIBAL(Hardware Architecture for Neural Networks Implementing Back propagation Algorithm Learning). For implementing an efficient neural network hardware, we analyzed various type of multiplier which is major function block of neuro-processor cell. With this result, we design a efficient digital neural network hardware using serial/parallel multiplier, and test the operation. We also analyze the hardware efficiency with logic level simulation. (author). refs., figs., tabs.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.170-175
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• 2001

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multiple objective genetic algorithm (MOGA), and a sample test case is presented to show the effects of optimizing the sequence with MOGA.

• 경영과학
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• 제14권2호
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• pp.47-61
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• 1997

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.