• Title/Summary/Keyword: penalty function method

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Process Optimization Formulated in GDP/MINLP Using Hybrid Genetic Algorithm (혼합 유전 알고리즘을 이용한 GDP/MINLP로 표현된 공정 최적화)

  • 송상옥;장영중;김구회;윤인섭
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.2
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    • pp.168-175
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    • 2003
  • A new algorithm based on Genetic Algorithms is proposed f3r solving process optimization problems formulated in MINLP, GDP and hybrid MINLP/GDP. This work is focused especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is experimented and many heuristics are adopted. Real and binary coded Genetic Algorithm initiates the global search in the entire search space and at every stage Simulated Annealing makes the candidates to climb up the local hills. Multi-Niche Crowding method is adopted as the multimodal function optimization technique. and the adaptation of probabilistic parameters and dynamic penalty systems are also implemented. New strategies to take the logical variables and constraints into consideration are proposed, as well. Various test problems selected from many fields of process systems engineering are tried and satisfactory results are obtained.

A Study on the design Optimization of Thickness of Machiningcenter Bed under Dynamic Loading by using Genetic Algorithm (유전적 알고리듬을 적용하여 머시닝센터 베드두께의 동하중을 고려한 최적설계에 관한 연구)

  • 조백희
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.8 no.1
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    • pp.67-73
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    • 1999
  • This paper presents resizing design optimization method by utilizing genetic algorithm(GA), which consists of three basic operators : reproduction, crossover and mutation. The fitness and penalty function for resizing optimization problem are defined, and the flowchart of the developed computer program along with the descriptions of each modules is presented. Also, modelling for flexible-body dynamic analysis is presented. The model is composed of bodies, joints, and force elements such as translational spring-damper-actuator. The design objects si to determine the wall thickness for minimum weight under dynamic displacement constraint.

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Traffic Assignment Incorporating Route Choice Behavior in Hierachical Highway Structure (도로위계구조를 고려한 노선배정기법에 관한 연구)

  • 김익기;김태중
    • Journal of Korean Society of Transportation
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    • v.13 no.3
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    • pp.19-33
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    • 1995
  • Conventional traffic assignment techniques usually do not consider traveler's route choice behavior affected by hierachicla strucfture in urban highway system. This study realizes the route choice behavior such that travelers tend to choose more higher level of highway rather than lower level of highway for longer trops. Otherwise, for shorter trips, travelers tend to choose lower level of highway unless they can get sufficient travel time saving by using mojor arterial street or freeway (higher level of highway). Therefore, this study suggests a traffic assignment technique incorrporating route choice behavior related to hierachical highway structure by introducing some perception costs to generalized cost function such as perceptional preference measureemnt for higher level higheay and perceptional penalty when changing to different level of highway. Through simulation analysis, it is shown that the simulation results with the new traffic assignment echnique can be different a lot from the results with the convential method.

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Design of $H_2$ and $H_{\infty}$ static output feedback controllers (정적출력궤환 $H_2$$H_{\infty}$ 제어기 설계)

  • Kim, Seog-Joo;Lee, Jong-Moo;Cheon, Jong-Min;Kwon, Soon-Man;Park, Min-Kook
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.2564-2566
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    • 2005
  • This paper presents an iterative linear matrix inequality (LMI) method for $H_2$ and $H_{\infty}$ optimal static output feedback (SOF) control, which is expressed in terms of LMIs subject to an additional rank condition. We propose a linear Penalty function to penalize the rank constraint so that static $H_2$ and $H_{\infty}$ synthesis results in solving a series of convex LMI optimization problems. Numerical experiments for various $H_2$ and $H_{\infty}$ SOF synthesis were performed to demonstrate the effectiveness of the proposed algorithm.

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Genetic Programming Approach to Curve Fitting of Noisy Data and Its Application In Ship Design (유전적 프로그래밍을 이용한 노이지 데이터의 Curve Fitting과 선박설계에서의 적용)

  • Lee K. H.;Yeun Y S.
    • Korean Journal of Computational Design and Engineering
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    • v.9 no.3
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    • pp.183-191
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    • 2004
  • This paper deals with smooth curve fitting of data corrupt by noise. Most research efforts have been concentrated on employing the smoothness penalty function with the estimation of its optimal parameter in order to avoid the 'overfilling and underfitting' dilemma in noisy data fitting problems. Our approach, called DBSF(Differentiation-Based Smooth Fitting), is different from the above-mentioned method. The main idea is that optimal functions approximately estimating the derivative of noisy curve data are generated first using genetic programming, and then their integral values are evaluated and used to recover the original curve form. To show the effectiveness of this approach, DBSP is demonstrated by presenting two illustrative examples and the application of estimating the principal dimensions of bulk cargo ships in the conceptual design stage.

An efficient method for nonlinear optimization problems using modified genetic algorithms (수정된 유전 알고리즘을 이용한 비선형최적화 문제의 효율적인 해법)

  • 윤영수;이상용
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.04a
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    • pp.519-524
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    • 1996
  • This paper describes the application of Genetic Algorithms(GAs) to nonlinear constrained mixed optimization problems. Genetic Algorithms are combinatorial in nature, and therefore are computationally suitable for treating discrete and integer design variables. But, several problems that conventional GAs are ill defined are applicaiton of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained optimization problem into an unconstrained one and premature convergence of solution. Thus, we developed an modified GAs to solve this problems, and two examples are given to demonstrate the effectiveness of the methodology developed in this paper.

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Adaptive Cutting Parameter Optimization Applied to Face Milling Operations (면삭 밀링공정에서의 절삭조건의 적응 최적화)

  • 고태조;조동우
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.3
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    • pp.713-723
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    • 1995
  • In intelligent machine tools, a computer based control system, which can adapt the machining parameters in an optimal fashion based on sensor measurements of the machining process, should be incorporated. In this paper, the technology for adaptively optimizing the cutting conditions to maximize the material removal rate in face milling operations is proposed using the exterior penalty function method combined with multilayered neural networks. Two neural networks are introduced ; one for estimating tool were length, the other for mapping input and output relations from experimental data. Then, the optimization of cutting conditions is adaptively implemented using tool were information and predicted process output. The results are demonstrated with respect to each level of machining such as rough, fine and finish cutting.

Modeling of Remediation Design in Theoretically Heterogeneous Domain

  • Ko, Nak-Youl;Lee, Kang-Kun
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2004.09a
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    • pp.302-306
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    • 2004
  • Probabilistic approaches are applied to the problem of groundwater remediation design to consider the risk of design and heterogeneity of real condition. Hydraulic conductivity fields are generated by two methods. First, the homogeneous domains which have the hydraulic conductivity with log-normal distribution are constructed by using Latin Hypercube method. Second, random fields with a certain spatial correlation are also generated. The optimal solutions represented by cumulative distribution function (CDF) of relative cost are calculated by three different manners. The one uses the homogeneous domains with the optimal design of base condition. It shows that ver)'wide range of cost and the influences of different penalty values. The other one uses the random field with same design and shows narrow range of cost. These CDF can reflect on the risk of optimal solution in a simple exampie condition and be effective in estimating the cost of groundwater remediation.

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Formulation of Knowledge Base for Fuzzy Network Performance Manager with Genetic Algorithm (유전자 알고리즘을 이용한 퍼지네트워크 성능관리기의 지식베이스 생성)

  • Lee, Sang-Ho;Kim, In-Jun;Lee, Kyung-Chang;Lee, Seok
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.514-518
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    • 1996
  • This paper focuses on automated generation of the knowledge base for a fuzzy network performance manager in order to satisfy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. Therefore, the bowlegs base is formulated to minimize a certain penalty function by using a type of genetic algorithm. The efficacy of the formulation method has been demonstrated by a series of simulation experiments.

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Adaptive finite element wind analysis with mesh refinement and recovery (요소 세분화 및 재결합을 이용한 바람의 적응적 유한요소 해석)

  • 최창근;유원진;이은진
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1998.04a
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    • pp.60-67
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    • 1998
  • This paper deals with the development of a variable-node element and its application to the adaptive h-version mesh refinement-recovery for the incompressible viscous flow analysis. The element which has variable mid-side nodes can be used in generating the transition zone between the refined and unrefined elements and efficiently used for construction of a refined mesh without generating distorted elements. A modified Gaussian quadrature is needed to evaluate the element matrices due to the discontinuity of derivatives of the shape functions used for the element. The penalty function method which can reduce the number of independent variables is adopted for the purpose of computational efficiency and the selective reduced integration is carried out for the convection and pressure terms to preserve the stability of solution. For the economical analysis of transient problems, not only the mesh refinement but also the mesh recovery is needed. The numerical examples show that the optimal mesh for the finite element analysis of a wind around the structures can be obtained automatically by the proposed scheme.

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