• Journal of Ocean Engineering and Technology
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• v.17 no.6
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• pp.53-57
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• 2003

Optimum design of most structural system requires that design variables are regarded as discrete quantities. This paper presents the use of Genetic Algorithm for determining the optimum design for truss with discrete variables. Genetic Algorithm are know as heuristic search algorithms, and are effective global search methods for discrete optimization. In this paper, Elitism and the method of conferring penalty parameters in the design variables, in order to achieve improved fitness in the reproduction process, is used in the Genetic Algorithm. A 10-Bar plane truss and a 25-Bar space truss are used for discrete optimization. These structures are designed for stress and displacement constraints, but buckling is not considered. In particular, we obtain continuous solution using Genetic Algorithms for a 10-bar truss, compared with other results. The effectiveness of Genetic Algorithms for global optimization is demonstrated through two truss examples.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.5
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• pp.345-350
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• 2011

This paper was carried about optimization for high efficiency of point contact solar cell. We have studied on the characteristics of power converter according to each parameter for the optimization for high efficiency of point contact solar cell on this study. We have 25.1352% of convert efficiency after adapt optimal parameters as mentioned in point body and superior conclusion is drawn by comparison with general efficiency has within 20%. At this time, the value of parameter is 100 um cell pitch, 0.01 um AR coating, 0.9 um N+ FSF thickness., etc. This study will continue to go on for optimization for efficiency in future, as it looks now, the results of this study would contribute to the business of high efficiency of point contact solar cell.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.123-130
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• 2006

In manufacturing, process automation and parameter optimization are required in order to improve productivity. Especially in welding process, productivity and weldablity should be considered to determine the process parameter. In this paper, optimization methodology was proposed to determine the welding conditions using the objective function in terms of productivity and weldablity. In order to conduct this, welding experiments were carried out. Tensile test was performed to evaluate the weldability. Neural network model to estimate tensile strength using the laser power, welding speed, and wire feed rate was developed. Objective function was defined using the normalized tensile strength which represented the weldablilty and welding speed and wire feed rate which represented the productivity. The optimal welding parameters which maximized the objective function were determined.

• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.447-456
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• 2007

The ant colony optimization (ACO) is a probabilistic Meta-heuristic algorithm which has been developed in recent years. Originally ACO was used for solving the well-known Traveling Salesperson Problem. More recently, ACO has been used to solve many difficult problems. In this paper, we develop an ant colony optimization method to solve the maximum independent set problem, which is known to be NP-hard. In this paper, we suggest a new method for local information of ACO. Parameters of the ACO algorithm are tuned by evolutionary operations which have been used in forecasting and time series analysis. To show the performance of the ACO algorithm, the set of instances from discrete mathematics and computer science (DIMACS)benchmark graphs are tested, and computational results are compared with a previously developed ACO algorithm and other heuristic algorithms.

• Structural Engineering and Mechanics
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• v.51 no.1
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• pp.67-88
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• 2014

It is shown that topology optimization is a valuable tool for the design of bridge girders. This paper is a follow-up to (Kuty${\l}$owski and Rasiak 2014) and it includes an analysis of truss members' outer dimensions dictated by the standards. Moreover, a frame bridge girder mapped from a selected topology is compared with a typical frame girder on the basis of (Kuty${\l}$owski and Rasiak 2014). The analysis shows that topology optimization by means of the proposed algorithm yields a topology from which one can map a frame bridge girder requiring less material for its construction than the typical frame girder currently used in bridge construction.

• The KSFM Journal of Fluid Machinery
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• v.17 no.3
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• pp.5-12
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• 2014

This paper presents a design optimization for meridional profile and blade angle ${\theta}$ of a centrifugal compressor with DOE (design of experiments) and RSM (response surface method). Control points of the $3^{rd}$ order Bezier curve are used for design parameters and specific overall efficiency is used as object function. The response surface function shows good agreement with the 3D computational results. Three different optimized designs are proposed and compared with reference design at design point and off-design point. Contours of relative Mach number, static entropy, and total pressure are analyzed for improvement of performance by optimization. Off-design performance analysis is conducted by total pressure and efficiency.

• Journal of computational fluids engineering
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• v.17 no.1
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• pp.16-22
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• 2012

Acoustic pressure field around the centrifugal fan is predicted by a aero-acoustic splitting method. Unsteady flow field is obtained by solving the incompressible Navier-Stokes equations using commercial code, while the acoustic waves generated inside the centrifugal fan and shroud are predicted by solving the far field acoustics analysis. Computational results show that the acoustic waves of BPF tone are generated by interactions of the blades with the shroud. Acoustic results is validated by experimental results This paper describes the influence of geometric parameters on the noise generation from the section of blades and shroud. One of the effective ways to reduce BPF noise is optimization method using Genetic Algorithm, which effectively minimize eccentricity, is suggested. New improving design was developed by optimization method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.1041-1049
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• 2003

In this paper, a new local two-point approximation method which is based on the exponential intervening variable is proposed. This new algorithm, called the Two-Point Convex Approximation(TPCA), use the function and design sensitivity information from the current and previous design points of the sequential approximate optimization to generate a sequence of convex, separable subproblems. This paper describes the derivation of the parameters associated with the approximation and the numerical solution procedure. In order to show the numerical performance of the proposed method, a sequential approximate optimizer is developed and applied to solve several typical design problems. These optimization results are compared with those of other optimizers. Numerical results obtained from the test examples demonstrate the effectiveness of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.940-947
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• 2004

In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen for design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size for each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem.