• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.4
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• pp.407-417
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• 2003

Enen though several GA-based optimization algorithms have been successfully applied to complex optimization problems in various engineering fields, GA-based optimization methods are computationally too expensive for practical use in the field of structural optimization, particularly for large- scale problems. Furthermore, a successful implementation of GA-based optimization algorithm requires a cumbersome and trial-and-error routine related to setting of parameters dependent on a optimization problem. Therefore, to overcome these disadvantages, a high-performance GA is developed in the form of distributed hybrid genetic algorithm for structural optimization on a cluster of personal computers. The distributed hybrid genetic algorithm proposed in this paper consist of a simple GA running on a master computer and multiple μ-GAs running on slave computers. The algorithm is implemented on a PC cluster and applied to the minimum weight design of steel structures. The results show that the computational time required for structural optimization process can be drastically reduced and the dependency on the parameters can be avoided.

• The KSFM Journal of Fluid Machinery
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• v.14 no.5
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• pp.63-68
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• 2011

This paper presents an optimization procedure for performance improvement of a tunnel ventilation jet fan. Optimization techniques based on response surface approximation (RSA) are employed to improve the aerodynamic performance of a tunnel ventilation jet fan. For numerical analysis, three-dimensional Renolds- averaged Navier-Stokes (RANS) equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the total efficiency at the operating condition as the objective function. Four geometric variables defining the meridional length and the thickness profile at the hub and shroud in the jet fan rotor are selected as design variables for the numerical optimization. The results of the numerical optimization show that the total efficiency of the optimized model is significantly improved in comparison with the base model.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.283-284
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• 2008

A cross-layer optimization is becoming a popular design methodology for the IP based next generation wireless network. We begin by investigating a cross-layer optimization scheme to enhance the system performance in wireless networks. By applying cross-layer optimization methodology to WiBro distributed network, the WiBro systems are expected to gain significant performance improvement and resource utilization enhanced. For further study we highlight some open challenges and new opportunities for cross-layer design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.9
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• pp.1462-1469
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• 1997

This study presents a genetic algorithm-based method for optimizing control parameters in fluid power systems. Genetic algorithms are general-purpose optimization methods based on natural evolution and genetics. A genetic algorithm seeks control parameters maximizing a measure that evaluates system performance. Five control gains of the PID-PD cascade controller fr an electrohydraulic speed control system with a variable displacement hydraulic motor are optimized using a genetic algorithm in the experiment. Optimized gains are confirmed by inspecting the fitness distribution which represents system performance in gain spaces. It is shown that optimization of the five gains by manual tuning should be a task of great difficulty and that a genetic algorithm is an efficient scheme giving economy of time and in labor in optimizing control parameters of fluid power systems.

• International Journal of Fluid Machinery and Systems
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• v.2 no.1
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• pp.1-12
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• 2009

Surrogate modeling is applied to a compressor blade shape optimization to modify its stacking line and thickness to enhance adiabatic efficiency and total pressure ratio. Six design variables are defined by parametric curves and three objectives; efficiency, total pressure and a combined objective of efficiency and total pressure are considered to enhance the performance of compressor blade. Latin hypercube sampling of design of experiments is used to generate 55 designs within design space constituted by the lower and upper limits of variables. Optimum designs are found by formulating a PRESS (predicted error sum of squares) based averaging (PBA) surrogate model with the help of a gradient based optimization algorithm. The optimum designs using the current variables show that, to optimize the performance of turbomachinery blade, the adiabatic efficiency objective is improved substantially while total pressure ratio objective is increased a very small amount. The multi-objective optimization shows that the efficiency can be increased with the less compensation of total pressure reduction or both objectives can be increased simultaneously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1319-1335
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• 2017

This paper proposes an opportunistic reporting-based sensing-reporting-throughput optimization scheme that maximizes the spectral efficiency of secondary users (SUs) in cooperative cognitive radio networks with a soft combining rule. The performance of cooperative spectrum sensing depends on the sensing time, the reporting time of transmitting sensing results, and the fusion scheme. While longer sensing time and reporting time improve the sensing performance, this shortens the allowable data transmission time, which in turn degrades the spectral efficiency of SUs. The proposed scheme adopts an opportunistic reporting scheme to restrain the reporting overhead and it jointly controls the sensing-reporting overhead in order to increase the spectral efficiency of SUs. We show that there is a trade-off between the spectral efficiency of SUs and the overheads of cooperative spectrum sensing. The numerical results demonstrate that the proposed scheme significantly outperforms the conventional sensing-throughput optimization schemes when there are many SUs. Moreover, the numerical results show that the sensing-reporting time should be jointly optimized in order to maximize the spectral efficiency of SUs.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1007-1014
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• 2015

An optimally designed six-phase induction motor (6PIM) is compared with an initial design induction motor having the same ratings. The Genetic Algorithm (GA) method is used for optimization and multi objective function is considered. Comparison of the optimum design with the initial design reveals that better performance can be obtained by a simple optimization method. Also in this paper each design of 6PIM, is simulated by MAXWELL_2D. The obtained simulation results are compared in order to find the most suitable solution for the specified application, considering the influence of each design upon the motor performance. Construction a 6PIM based on the information obtained from GA method has been done. Quality parameters of the designed motors, such as: efficiency, power losses and power factor measured and optimal design has been evaluated. Laboratory tests have proven the correctness of optimal design.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1122-1130
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• 2000

Based on the value of the Lagrange multiplier and the degree of constraint activeness, a new update rule is proposed for penalty parameters of the ALM method. The theoretical exposition of this suggested update rule is presented by using the algorithmic interpretation and the geometric interpretation of the augmented Lagrangian. This interpretation shows that the penalty parameters can effect the performance of the ALM method. Also, it offers a lower limit on the penalty parameters that makes the augmented Lagrangian to be bounded. This lower limit forms the backbone of the proposed update rule. To investigate the numerical performance of the update rule, it is embedded in our ALM based dynamic response optimizer, and the optimizer is applied to solve six typical dynamic response optimization problems. Our optimization results are compared with those obtained by employing three conventional update rules used in the literature, which shows that the suggested update rule is more efficient and more stable than the conventional ones.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1763-1768
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• 2003

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. Based on the independence axiom of axiomatic design theory that illustrates the relationship between desired specifications and design parameters, the designs can be classified into three types: uncoupled, decoupled and coupled. To best approach the target performance with the maximum robustness is one of the main functional requirements of a mechanical system. Most engineering designs are pertaining to either coupled or decoupled ones, but these designs cannot currently accomplish a real robustness thus a trade-off between performance and robustness has to be made. In this research, the game theory will be applied to optimize the trade-off.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.491-496
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• 2005

A pump design system was constructed by several integrating in-house programs and commercial softwares to design and evaluate centrifugal pumps. An agent-based prototype framework has been developed for collaborative design and optimization of a centrifugal pump. This paper introduces the feasible technology needed to construct a pump design system based on software agents. The integrated design system, developed in the present study, was used in designing a centrifugal pump and modifying its impeller shape by using optimization processes to increase the pump performance.