• Proceedings of the KSME Conference
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• 2005.11a
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• pp.52.1-52.1
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• 2005

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.43-52
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• 2004

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algerian was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.10 s.101
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• pp.995-1002
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• 2005

An orthogonal frequency division multiplexing(OFDM) system has the problem of the peak-to-average power ratio(PAR). In general, in order to obtain optimal PAR reduction using the partial transmitted sequence(PTS), the total search for the number of sub-blocks and the rotation factors must be accomplished. As the number of sub-blocks and rotation factors increases, PAR reduction improves, such that complexity increases exponentially and the process delay occurs simultaneously. Therefore a technique that reduces PAR, which is almost close to optimal, and the amount of calculation is desired. In this paper a new method using genetic algorithm(GA), which is widely used to search for a point that is globally optimal in many problems, is proposed to search for a rotation factor that reduces simultaneously both the PAR and the amount of calculation, such that the complexity of calculation and the process time are reduced at the same time, Comparison is performed between the proposed method and the various techniques developed previously. The superiority of proposed method is presented by demonstrating the reduction of complexity while a similar PAR reduction is obtained.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.273-280
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• 2005

The design of structural engineering optimization is to minimize the cost. This problem has many objective functions formulating section and shape as a function of the included discrete variables. simulated annealing, genetic algerian and TABU algerian are searching methods for optimum values. The object of this reserch Is comparing the result of TABU algorithm, and verifying the efficiency of TABU algorithm in structural optimization design field. For the purpose, this study used a solid truss of 25 elements having 10 nodes, and size optimization for each constraint and load condition of Geodesic ome, and shape optimization of Cable Dome for verifying spatial structures by the application of TABU algorithm.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.25-32
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• 2004

This paper presents a new optimization technique of acceleration curve for dynamic structure's movement in which high speed and low vibration are desirable. This technique is based on a genetic algerian with a penalty function for acceleration optimization under the assumption that an initial profile of acceleration curves constitutes the first generation of the genetic algorithm. Especially the penalty function consists of the violation of constraints and the number of violated constraints. The optimized acceleration of the crane through the genetic algorithm and commercial dynamic analysis software has shown to have accurate movement and low vibration compared to the conventional accelerations with jerk discontinuity.

• Proceeding of KASS Symposium
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• 2005.05a
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• pp.246-253
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• 2005

The design of structural engineering optimization is to minimize the cost. This problem has many objective functions formulating section and shape as a function of the included discrete variables. simulated annealing, genetic algerian and TABU algorithm are searching methods for optimum values. The object of this reserch is comparing the result of TABU algorithm, and verifying the efficiency of TABU algorithm in structural optimization design field. For the purpose, this study used a solid truss of 25 elements having 10 nodes, and size optimization for each constraint and load condition of Geodesic one, and shape optimization of Cable Dome for verifying spatial structures by the application of TABU algorithm

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1840-1846
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• 2005

In this paper, does by purpose DC servo motor speed controller design about PID coefficient tuning techniques that use genetic algerian. DC servo motor is used in application field of a peat many control machine or robot etc. and in this field, selection of controller parameters requires user's expert knowledge. Therefore, general amount of work engineers must continuously iteration tuning in controller parameters by trial and error. With this, when must tuning parameter coefficient about change of dynamic system or disturbance, can improve the efficiency according to following that is more precised and parameter coefficient value that is optimized by using genetic algorithm. In this paper, from dynamic character modeling get in analyze dynamic character of DC motor desist controller drive control possible that is fast response character md improved speed precision using a Genetic Algorithms.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.55-65
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• 2009

Due to the rapid increase of electricity demand, consideration of environmental constraints in optimal power flow (OPF) problems is increasingly important. In Algeria, up to 90% of electricity is produced by thermal generators (vapor, gas). In order to keep the emission of gaseous pollutants like sulfur dioxide (SO2) and Nitrogen (NO2) under the admissible ecological limits, many conventional and global optimization methods have been proposed to study the trade-off relation between fuel cost and emissions. This paper presents an efficient decomposed Parallel GA to solve the multi-objective environmental/economic dispatch problem. At the decomposed stage the length of the original chromosome is reduced successively and adapted to the topology of the new partition. Two subproblems are proposed: the first subproblem is related to the active power planning to minimize the total fuel cost, and the second subproblem is a reactive power planning design based in practical rules to make fine corrections to the voltage deviation and reactive power violation using a specified number of shunt dynamic compensators named Static Var Compensators (SVC). To validate the robustness of the proposed approach, the algorithm proposed was tested on the Algerian 59-bus network test and compared with conventional methods and with global optimization methods (GA, FGA, and ACO). The results show that the approach proposed can converge to the near solution and obtain a competitive solution at a critical situation and within a reasonable time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.5 s.311
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• pp.44-59
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• 2006

This paper describes the efficient implementation of DNA sequence generate system with genetic algorithm for reducing computation time of NACST. The proposed processor is based on genetic algerian with fitness functions which would suit the point of reference for generated sequences. In order to implement efficient hardware structure, we used the pipelined structure. In addition our design was applied the parallelism to achieve even better simulation time than the sequence generator system which is designed on software. In this paper, our hardware is implemented on the FPGA board with xc2v6000 devices. Through experiment, the proposed hardware achieves 467 times speed-up over software on a PC and sequence generate performance of hardware is same with software.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.