• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.739-744
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• 2012

The genetic algorithm (GA) is regarded as one of the best ways for determining a global solution. Because it does not require calculating the design sensitivity differently from the ordinary gradient-based method, it is appropriate for the design problem in the ultra-high frequency range; the ordinary gradient-based method has difficulty in calculating the sensitivity in this range. This paper deals with nano-aperture grating topology optimization based on the GA and the ON/OFF method. The objective of this study is to maximize the transmittance in the measuring area. The simulation and optimization processes are carried out by using the commercial package COMSOL associated with Matlab programming. The final optimal design gives around 21% performance improvement, compared with the initial model.

• Geomechanics and Engineering
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• v.20 no.3
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• pp.191-205
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• 2020

Soil shear strength parameters play a remarkable role in designing geotechnical structures such as retaining wall and dam. This study puts an effort to propose two accurate and practical predictive models of soil shear strength parameters via hybrid artificial neural network (ANN)-based models namely genetic algorithm (GA)-ANN and particle swarm optimization (PSO)-ANN. To reach the aim of this study, a series of consolidated undrained Triaxial tests were conducted to survey inherent strength increase due to addition of polypropylene fibers to sandy soil. Fiber material with different lengths and percentages were considered to be mixed with sandy soil to evaluate cohesion (as one of shear strength parameter) values. The obtained results from laboratory tests showed that fiber percentage, fiber length, deviator stress and pore water pressure have a significant impact on cohesion values and due to that, these parameters were selected as model inputs. Many GA-ANN and PSO-ANN models were constructed based on the most effective parameters of these models. Based on the simulation results and the computed indices' values, it is observed that the developed GA-ANN model with training and testing coefficient of determination values of 0.957 and 0.950, respectively, performs better than the proposed PSO-ANN model giving coefficient of determination values of 0.938 and 0.943 for training and testing sets, respectively. Therefore, GA-ANN can provide a new applicable model to effectively predict cohesion of fiber-reinforced sandy soil.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• Journal of Ship and Ocean Technology
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• v.5 no.2
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• pp.14-26
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• 2001

This paper presents a novel design approach that could generate structural design alternatives having different topologies and then, select the optimum structure from them with simulataneously determining its optimum design variables related to geometry and the member size subjected to the multiple objective design environments. For this purpose, a specialized genetic algorithm, called StrGA_DeAl + MOGA, which can handle the design alternatives and multi-criteria problems very effectively, is developed for the optimal structural design. To validate the developed method, method, plain truss design problems are considered as illustrative example. To begin with, some possible topological of the truss structure are suggested based on the stability criterion that should be satisfied under the given loading condition. Then, with the consideration of the given multi-criteria, several different topology forms are selected as design alternatives for the second step of the conceptual design process. Based on the chosen topolgy of truss structures, the sizing or shaping optimization process starts to determine the optimum design parameters. Ten-bar truss problems are given in the paper to confirm the above concept and methodology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1551-1558
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• 2021

Beacon signals used in indoor positioning system are reflected and distorted, resulting in noise signals. KF(Kalman Filter) has been widely used to remove this noise. In order to apply the KF, optimization process considering the signal type, signal strength, and environmental elements of each product is required. In this paper, we propose a solution to the optimization problem of KF Parameters using GA(Genetic Algorithm) in BLE(Bluetooth Low Energy) Beacon-based indoor positioning system. After optimizing KF Parameters by applying the proposed technique with a certain distance between Beacon and receiver, we compared the estimated distance passed through KF with the unfiltered distance. The proposed technique is expected to reduce the time required and improve accuracy of KF Parameters optimization in an indoor positioning system based on RSSI (Received Signal Strength Indication).

• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.6-13
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• 2001

A new GA-3D-PTV technique has been constructed to measure an impinging jet. The measurement system consists of three CCD cameras, Ar-ion laser, an image grabber and a host computer. GA (Genetic Algorithm) was used based on one-to-one correspondences in order to take advantage of the combinatorial optimization in tracking the pairs of the whole particles of the two images having a time interval. Two fitness functions were introduced in order to enhance the correspondences of the particles. One was based on a concept of the continuum theory and the other one was based on a minimum distance error. The constructed GA-3D-PTV system was applied in success to the measurement of flow characteristics of the impinging jet.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.430-438
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• 2004

Among the optimization method, GA (genetic algorithm) is a very powerful searching method enough to compete with design sensitivity analysis method. GA is very easy to apply, since it dose not require any design sensitivity information. However, GA has been computationally not efficient due to huge repetitive computation. In this study, parallel computation is adopted to Improve computational efficiency, Paralleled GA is introduced on a clustered LINUX based personal computer system.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.189-196
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• 2003

Among the optimization method, GA (genetic algorithm) is a very powerful searching method enough to compete with design sensitivity analysis method. GA is very easy to apply, since it dose not require any design sensitivity information. However, GA has been computationally not efficient due to huge repetitive computation. In this study, parallel computation is adopted to improve computational efficiency. Paralleled GA is introduced on a clustered LINUX based personal computer system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.10
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• pp.149-156
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• 2010

In this paper, the optimal design of a wind generator, implemented with the hybridized GA(Genetic Algorithm) and ES(Expert System), has been performed to maximize the AEP(Annual Energy Production) over the whole wind speed characterized by the statistical model of wind speed distribution. In particular, to solve the problem of calculation iterate, ES finds the superior individual and apply to initial generation of GA and it makes reduction of search domain. Meanwhile, for effective searching in reduced search domain, it propose Intelligent GA algorithm. Also, it shows the results of optimized model 500[kW] wind generator using hybridized algorithm and benchmark result of compare with GA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1149-1160
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• 2005

Generally, the network topology design problem, which is difficult to solve with the classical method because it has exponentially increasing complexity with the augmented network size, is characterized as a kind of NP-hard combinatorial optimization problem. The problem of this research is to design the highly reliable network topology considering the connection cost and all-terminal network reliability, which can be defined as the probability that every pair of nodes can communicate with each other. In order to solve the highly reliable network topology design problem minimizing the construction cost subject to network reliability, we proposes an efficient two phase approach to design reliable network topology, i.e., the first phase employs, a genetic algorithm (GA) which uses $Pr\ddot{u}fer$ number for encoding method and backtracking Algorithm for network reliability calculation, to find the spanning tree; the second phase is a greedy method which searches the optimal network topology based on the spanning ree obtained in the first phase, with considering 2-connectivity. finally, we show some experiments to demonstrate the effectiveness and efficiency of our two phase approach.