• Title, Summary, Keyword: real-coded genetic algorithm

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Simulation Optimization of Manufacturing System using Real-coded Genetic Algorithm (실수 코딩 유전자 알고리즘을 이용한 생산 시스템의 시뮬레이션 최적화)

  • Park, Kyoung-Jong
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.28 no.3
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    • pp.149-155
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    • 2005
  • In this paper, we optimize simulation model of a manufacturing system using the real-coded genetic algorithm. Because the manufacturing system expressed by simulation model has stochastic process, the objective functions such as the throughput of a manufacturing system or the resource utilization are not optimized by simulation itself. So, in order to solve it, we apply optimization methods such as a genetic algorithm to simulation method. Especially, the genetic algorithm is known to more effective method than other methods to find global optimum, because the genetic algorithm uses entity pools to find the optimum. In this study, therefore, we apply the real-coded genetic algorithm to simulation optimization of a manufacturing system, which is known to more effective method than the binary-coded genetic algorithm when we optimize the constraint problems. We use the reproduction operator of the applied real-coded genetic algorithm as technique of the remainder stochastic sample with replacement and the crossover operator as the technique of simple crossover. Also, we use the mutation operator as the technique of the dynamic mutation that configures the searching area with generations.

Model-based Tuning Rules of the PID Controller Using Real-coded Genetic Algorithms (RCGA를 이용한 PID 제어기의 모델기반 동조규칙)

  • 김도응;진강규
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.12
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    • pp.1056-1060
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    • 2002
  • Model-based tuning rules of the PID controller are proposed incorporating with real-coded genetic algorithms. The optimal parameter sets of the PID controller for step set-point tracking are obtained based on the first-order time delay model and a real-coded genetic algorithm as an optimization tool. As for assessing the performance of the controllers, performance indices(ISE, IAE and ITAE) are adopted. Then tuning rules are derived using the tuned parameter sets, potential rule models and another real-coded genetic algorithm A set of simulation works is carried out to verify the effectiveness of the proposed rules.

Real-coded Micro-Genetic Algorithm for Nonlinear Constrained Engineering Designs

  • Kim Yunyoung;Kim Byeong-Il;Shin Sung-Chul
    • Journal of Ship and Ocean Technology
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    • v.9 no.4
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    • pp.35-46
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    • 2005
  • The performance of optimisation methods, based on penalty functions, is highly problem- dependent and many methods require additional tuning of some variables. This additional tuning is the influences of penalty coefficient, which depend strongly on the degree of constraint violation. Moreover, Binary-coded Genetic Algorithm (BGA) meets certain difficulties when dealing with continuous and/or discrete search spaces with large dimensions. With the above reasons, Real-coded Micro-Genetic Algorithm (R$\mu$GA) is proposed to find the global optimum of continuous and/or discrete nonlinear constrained engineering problems without handling any of penalty functions. R$\mu$GA can help in avoiding the premature convergence and search for global solution-spaces, because of its wide spread applicability, global perspective and inherent parallelism. The proposed R$\mu$GA approach has been demonstrated by solving three different engineering design problems. From the simulation results, it has been concluded that R$\mu$GA is an effective global optimisation tool for solving continuous and/or discrete nonlinear constrained real­world optimisation problems.

Coefficient Estimation of IIR Digital Filters Using a Real-Coded Genetic Algorithm

  • Lee, Yun-Hyung;So, Myung-Ok;Jin, Gang-Gyoo;Rhyu, Keel-Soo
    • Journal of the Korean Society of Marine Engineering
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    • v.31 no.7
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    • pp.863-871
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    • 2007
  • This paper proposes a methodology to estimate the system coefficients for the infinite impulse response(IIR) digital filters using real code GA. In the traditional real coded GA, it adapts the general genetic operations, whereas in this paper the proposed real coded GA applies improved genetic operations in order to search the optimal solution in given problems. Each of unknown IIR digital coefficients collected as forms of a chromosome. Two illustrative examples including the band pass and band stop IIR digital filters are demonstrated to verify the proposed method.

System Identification by Real-Coded Genetic Algorithm (실수코딩 유전알고리즘을 이용한 시스템 식별)

  • Ahn, Jong-Kap;Lee, Yun-Hyung;Jin, Gang-Gyoo;So, Myung-Ok
    • Journal of the Korean Society of Marine Engineering
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    • v.31 no.5
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    • pp.599-605
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    • 2007
  • This paper presents a method for identifying various systems based on input-output data and a real-coded genetic algorithm(RCGA). The advantages of this technique are, first, it is not dependent on the deterministic or stochastic nature of the systems and, second, the globally optimized models for the original systems can be identified without the need of a differentiable measure function of linearly separable parameters. Under suitable hypotheses, the estimation error is shown to converge in probability to zero. The performance of the proposed algorithm is demonstrated through several simulations.

Reliability-based design optimization of structural systems using a hybrid genetic algorithm

  • Abbasnia, Reza;Shayanfar, Mohsenali;Khodam, Ali
    • Structural Engineering and Mechanics
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    • v.52 no.6
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    • pp.1099-1120
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    • 2014
  • In this paper, reliability-based design optimization (RBDO) of structures is addressed. For this purpose, the global search and optimization capabilities of genetic algorithm (GA) are combined with the efficiency and reasonable accuracy of an advanced moment-based finite element reliability method. For performing RBDO, three variants of GA including a real-coded, a binary-coded and an improved binary-coded GA are developed. In these methods, GA performs (finite element) reliability analyses to evaluate reliability constraints. For truss structures which include finite element modeling, reliability constraints are evaluated using finite element reliability analysis. Response sensitivity required for finite element reliability analysis is obtained by direct differentiation method (DDM) rather than finite difference method (FDM). The proposed methods are examined within four standard test examples and real-world design problems. The results illustrate the superiority and efficiency of the improved binary-coded GA. Results also illustrate that DDM significantly reduces the computational cost and improves the efficiency of the optimization procedure.

Optimum Design of Torsional Shafting Using Real-Coded Genetic Algorithm (실수코딩 유전알고리즘을 이용한 비틀림 축계의 최적설계)

  • 최명수;문덕홍;설종구
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.39 no.4
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    • pp.284-290
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    • 2003
  • It is very important to minimize the weight of shaft from the viewpoint of economics and manufacture. For minimizing effectively the diameter of shaft in torsional shafting, authors developed computer program using the real-coded genetic algorithm which is one of optimizing techniques and based on real coding representation of genetic algorithm. In order to confirm the accuracy and effectiveness of the developed computer program, the computational results by the developed program were compared with those of conventional strength, stiffness and vibration designs for a generator shafting.

Control of Unstable Systems Concerned with the Performance Indexes and Constraints (성능지수와 제약조건을 고려한 불안정 시스템의 제어)

  • Ahn, Jong-Kap;Lee, Yun-Hung;So, Myung-Ok
    • Journal of the Korean Society of Marine Engineering
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    • v.32 no.5
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    • pp.785-790
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    • 2008
  • A technique for determining the feedback gain of the states feedback controller using a real-coded genetic algorithm(RCGA) is presented. It is concerned with the states error to the performance index of a RCGA. As for assessing the performance of the controller three performance criteria (ISE. IAE and ITAE) are adopted. And designing the controller involves a constrained optimization problem. Therefore a real-coded genetic algorithm incorporating the penalty strategy is used. The performance of the proposed method is demonstrated through a set of simulation about an inverted pendulum system.

A Study on a Real-Coded Genetic Algorithm (실수코딩 유전알고리즘에 관한 연구)

  • Jin, Gang-Gyoo;Joo, Sang-Rae
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.4
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    • pp.268-275
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    • 2000
  • The increasing technological demands of today call for complex systems, which in turn involve a series of optimization problems with some equality or inequality constraints. In this paper, we presents a real-coded genetic algorithm(RCGA) as an optimization tool which is implemented by three genetic operators based on real coding representation. Through a lot of simulation works, the optimum settings of its control parameters are obtained on the basis of global off-line robustness for use in off-line applications. Two optimization problems are Presented to illustrate the usefulness of the RCGA. In case of a constrained problem, a penalty strategy is incorporated to transform the constrained problem into an unconstrained problem by penalizing infeasible solutions.

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Real-coded genetic algorithm for identification of time-delay process

  • Shin, Gang-Wook;Lee, Tae-Bong
    • 제어로봇시스템학회:학술대회논문집
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    • pp.1645-1650
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    • 2005
  • FOPDT(First-Order Plus Dead-Time) and SOPDT(Second-Order Plus Dead-Time) process, which are used as the most useful process in industry, are difficult about process identification because of the long dead-time problem and the model mismatch problem. Thus, the accuracy of process identification is the most important problem in FOPDT and SOPDT process control. In this paper, we proposed the real-coded genetic algorithm for identification of FOPDT and SOPDT processes. The proposed method using real-coding genetic algorithm shows better performance characteristic comparing with the existing an area-based identification method and a directed identification method that use step-test responses. The proposed strategy obtained useful result through a number of simulation examples.

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