• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.397-414
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• 2005

In the existing literature, most of the purchasing models were developed only for retailers problem ignoring the constraint of storage capacity of retailers shop/showroom. In this paper, we have developed a deterministic model of wholesaler-retailers' problem of single product. The storage capacity of wholesaler's warehouse/showroom and retailers' showroom/shop are assumed to be finite. The items are transported from wholesaler's warehouse to retailers' Own Warehouse (OW) in a lot. The customer's demand is assumed to be displayed inventory level dependent. Demands are met from OW and that spaces of OW will immediately be filled by shifting the same amount from the Rented Warehouse (RW) till the RW is empty. The time duration between selling from OW and filling up its space by new ones from RW is negligible. According to relative size of the retailers' existing (own) warehouse capacity and the demand factors, different scenarios are identified. Our objectives are to optimize the cost functions of wholesaler and two retailers separately. To solve this problem, a real coded Genetic Algorithm (GA) with roulette wheel selection/reproduction, whole arithmetic crossover and non-uniform mutation is developed. Finally a numerical example is presented to illustrate the results for different scenarios. To compare the results of GA, Generalised Reduced Gradient Method has been used for the problem. Also, a sensitivity analysis has been performed to study the variations of the optimal average cost with respect to the different parameters.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.145-152
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• 1999

This paper presents an optimal design method for fuzzy logic controllers using genetic algorithms. In general, the design of fuzzy logic controllers has difficulties in the acquisition of exper's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored, and parameters of the fuzzy logic controller obtained by expert's control action may not be global. To solve these problems, the proposed method using genetic algorithms in this paper, can tune the parameters of fuzzy logic controller including scaling factors and determine the appropriate number of fuzzy reles systematically and automatically. We provide the second drder dead time plant and inverted pendulum system to evaluate the feasibility and generality of our proposed method. Comparison shows that the proposed controller can producd higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controller.

• Transactions of Materials Processing
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• v.16 no.4 s.94
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• pp.250-253
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.19-28
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• 2011

Level design is one of the important factors in tower defense game development. The difficulty of tower defense game depends on its wave design. In general, it requires a lot of manual labor to generate well-balanced waves with fun. In this paper, we propose a new automated wave generation system by using a genetic algorithm. With our system, a game designer can easily generate an optimized wave by designating the difficulty level in the initial stage of game design. Our system can be useful in reducing the trial-errors in the initial level design process of tower defense game development.

• Molecules and Cells
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• v.25 no.3
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• pp.438-445
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• 2008

Leaf senescence is a highly regulated genetic process that constitutes the last stage of plant development and provides adaptive fitness by relocating metabolites from senescing leaves to reproducing seeds. Characterization of various senescence mutants, mostly in Arabidopsis, and genome-wide analyses of gene expression, have identified a wide array of regulatory components, including transcription factors and enzymes as well as signaling molecules mediating growth hormones and environmental stress responses. In this work we demonstrate that a membrane-associated NAC transcription factor, NTL9, mediates osmotic stress signaling in leaf senescence. The NTL9 gene is induced by osmotic stress. Furthermore, activation of the dormant, membrane-associated NTL9 is elevated under the same conditions. A series of senescence-associated genes (SAGs) were upregulated in transgenic plants overexpressing an activated form of NTL9, and some of them were slightly but reproducibly downregulated in a T-DNA insertional NTL9 knockout mutant. These observations indicate that NTL9 mediates osmotic stress responses that affect leaf senescence, providing a genetic link between intrinsic genetic programs and external signals in the control of leaf senescence.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.4
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• pp.445-450
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• 2007

An optimum design process of the broad-band multi-layered radar absorbing material, using genetic algorithm, is established for the radar cross section reduction of a complex target, which consists of multiple reflection structures, such as surface warships. It follows the successive process of radar cross section analysis, scattering center analysis, radar absorbing material design, and reanalysis of radar cross section after applying the radar absorbing material. It is demonstrated that it is very effective even in the optimum design of the multi-layer radar absorbing material. This results from the fact that the three factors, i.e.. the incident angle range, broad-band frequencies, and maximum thickness can be simultaneously taken into account by adopting the genetic algorithm.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.178-187
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• 2007

One important issue in power systems is dynamic instability due to loosing balance relation between electrical generation and a varying load demand that justifies the necessity of stabilization. Moreover, Power System Stabilizer (PSS) must have capability of producing appropriate stabilizing signals over a wide range of operating conditions and disturbances. To overcome these drawbacks, this paper proposes a new method for robust design of PSS by using an auto-tuning fuzzy control in combination with Real-Coded Genetic Algorithm (RCGA). This method includes two fuzzy controllers; internal fuzzy controller and supervisor fuzzy controller. The supervisor controller tunes the internal one by on-line applying of nonlinear scaling factors to inputs and outputs. The RCGA-based method is used for off-line training of this supervisor controller. The proposed PSS is tested in three operational conditions; nominal load, heavy load, and in the case of fault occurrence in transmission line. The simulation results are provided to compare the proposed PSS with conventional fuzzy PSS and conventional PSS. By evaluating the simulation results, it is shown that the performance and robustness of proposed PSS in different operating conditions is more acceptable

• Journal of Plant Biotechnology
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• v.37 no.4
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• pp.456-464
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• 2010

Potato is one of the most important crops in the world. Due to vegetative propagation of this crop, techniques of plant tissue culture and genetic transformation are often applied for potato researches and a lot of progress has been made in the breeding programs using these techniques during the last decades. In potato, there have been several trials to introduce GM potato varieties to the world market, but they so far failed due to the changed legislation and unwillingness of large processors to process GM potatoes. These issues are highly associated with the general acceptances of the public and other political decisions. In addition to these, there are still obstacles to overcome to achieve the development of commercial potato variety and several factors to improve horticulturally important traits. In this study, therefore, we reviewed recent advances and research status on tissue culture and genetic transformation in potato and discussed future perspective.

• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.371-376
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• 2009

In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.

• Journal of Welding and Joining
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• v.28 no.5
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• pp.99-105
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• 2010

Inverter DC resistance spot welding process has been very widely used for joining such as automotive body sheet metal. Because the lobe area of DC welding is larger than AC welding and DC welding has low electrode wear. So the use of Inverter DC resistance spot welding process has been further increased. And the application of high tensile steel is growing for light weight vehicle. To improve the weldability of high strength steel, the development of Inverter DC resistance spot welding system is more conducted. However, Inverter DC resistance spot welding system has a few problems. Current waveform is unstable and the expulsion has been occurred by characteristics of steel. In this study, inverter DC resistance spot welding system was made. And Fuzzy control algorithm was applied for constant current. The genetic algorithm was applied to optimize the fuzzy scaling factors, in order to optimize the fuzzy control.