• Title/Summary/Keyword: Genetic Algorithm Optimization

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(m, n)중 연속(r, s) : F 시스템의 정비모형에 대한 개미군집 최적화 해법 (Ant Colony Optimization Approach to the Utility Maintenance Model for Connected-(r, s)-out of-(m, n) : F System)

  • 이상헌;신동열
    • 산업공학
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    • 제21권3호
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    • pp.254-261
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    • 2008
  • Connected-(r,s)-out of-(m,n) : F system is an important topic in redundancy design of the complex system reliability and it's maintenance policy. Previous studies applied Monte Carlo simulation and genetic, simulated annealing algorithms to tackle the difficulty of maintenance policy problem. These algorithms suggested most suitable maintenance cycle to optimize maintenance pattern of connected-(r,s)-out of-(m,n) : F system. However, genetic algorithm is required long execution time relatively and simulated annealing has improved computational time but rather poor solutions. In this paper, we propose the ant colony optimization approach for connected-(r,s)-out of-(m,n) : F system that determines maintenance cycle and minimum unit cost. Computational results prove that ant colony optimization algorithm is superior to genetic algorithm, simulated annealing and tabu search in both execution time and quality of solution.

Development of Real Coded Genetic Algorithm for Multiperiod Optimization

  • Chang, Young-Jung;Song, Sang-Ok;Song, Ji-Ho;Dongil Shin;S. Ando
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.396-396
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    • 2000
  • Multiperiod optimization is the key step to tackle the supply chain optimization problems. Taking supply and demand uncertainty or prediction into consideration during the process synthesis phase leads to the maximization of the profit for the long range time horizon. In this study, new algorithm based on the Genetic Algorithms is proposed for multiperiod optimization formulated in MINLP, GDP and hybrid MINLP/GDP. In this study, the focus is given 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 tried. and many heuristics are adopted for this purpose.

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Application of multi objective genetic algorithm in ship hull optimization

  • Guha, Amitava;Falzaranoa, Jeffrey
    • Ocean Systems Engineering
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    • 제5권2호
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    • pp.91-107
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    • 2015
  • Ship hull optimization is categorized as a bound, multi variable, multi objective problem with nonlinear constraints. In such analysis, where the objective function representing the performance of the ship generally requires computationally involved hydrodynamic interaction evaluation methods, the objective functions are not smooth. Hence, the evolutionary techniques to attain the optimum hull forms is considered as the most practical strategy. In this study, a parametric ship hull form represented by B-Spline curves is optimized for multiple performance criteria using Genetic Algorithm. The methodology applied to automate the hull form generation, selection of optimization solvers and hydrodynamic parameter calculation for objective function and constraint definition are discussed here.

Weight minimum design of concrete beam strengthened with glass fiber reinforced polymer bar using genetic algorithm

  • Rahman, Md. Moshiur;Jumaat, Mohd Zamin;Islam, A.B.M. Saiful
    • Computers and Concrete
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    • 제19권2호
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    • pp.127-131
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    • 2017
  • This paper presents a generalized formulation for optimizing the design of concrete beam reinforced with glass fiber reinforced polymer bar. The optimization method is formulated to find the design variables leading to the minimum weight of concrete beam with constraints imposed based on ACI code provisions. A simple genetic algorithm is utilized to solve the optimization task. The weights of concrete and glass fiber reinforced polymer bar are included in the formulation of the objective function. The ultimate limit states and the serviceability limit states are included in formulation of constraints. The results of illustrated example demonstrate the efficiency of the proposed method to reduce the weight of beam as well as to satisfy the above requirement. The application of the optimization based on the most economical design concept have led to significant savings in the amount of the component materials to be used in comparison to classical design solutions.

Numerical Optimization of the Turbine Blade Leaning Angle Using the Parallel Genetic Algorithm

  • Lee, Eun-Seok;Jeong, Yong-Hyun;Park, Soon-Young
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2008년 영문 학술대회
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    • pp.686-689
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    • 2008
  • The leaning angle optimization of turbine blade using the genetic algorithm was conducted in this paper. The calculation CFD technique was based upon the Diagonalized Alternating Directional Implicit scheme(DADI) with algebraic turbulence modeling. The leaning angle of VKI turbine blade was represented using B-spline curve. The control points are the design variable. Genetic algorithm was taken into account as an optimization tool. The objective was to minimize the total pressure loss. The optimized final geometry shows the better aerodynamic performance compared with the initial turbine blade.

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Optimum design of steel space frames with composite beams using genetic algorithm

  • Artar, Musa;Daloglu, Ayse T.
    • Steel and Composite Structures
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    • 제19권2호
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    • pp.503-519
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    • 2015
  • This paper presents an optimization process using Genetic Algorithm (GA) for minimum weight by selecting suitable standard sections from a specified list taken from American Institute of Steel Construction (AISC). The stress constraints obeying AISC-LRFD (American Institute of Steel Construction-Load and Resistance Factor Design), lateral displacement constraints being the top and inter-storey drift, mid-span deflection constraints for the beams and geometric constraints are considered for optimum design by using GA that mimics biological processes. Optimum designs for three different space frames taken from the literature are carried out first without considering concrete slab effects in finite element analyses for the constraints above and the results are compared with the ones available in literature. The same optimization procedures are then repeated for the case of space frames with composite (steel and concrete) beams. A program is coded in MATLAB for the optimization processes. Results obtained in the study showed that consideration of the contribution of the concrete on the behavior of the floor beams results with less steel weight and ends up with more economical designs.

가변 벌점함수 유전알고리즘을 이용한 고정밀 양면 연삭기 구조물의 경량 고강성화 최적설계 (Structural Design Optimization of a High-Precision Grinding Machine for Minimum Compliance and Lightweight Using Genetic Algorithm)

  • 홍진현;박종권;최영휴
    • 한국정밀공학회지
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    • 제22권3호
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    • pp.146-153
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    • 2005
  • In this paper, a multi-step optimization using genetic algorithm with variable penalty function is introduced to the structural design optimization of a grinding machine. The design problem, in this study, is to find out the optimum configuration and dimensions of structural members which minimize the static compliance, the dynamic compliance, and the weight of the machine structure simultaneously under several design constraints such as dimensional constraints, maximum deflection limit, safety criterion, and maximum vibration amplitude limit. The first step is shape optimization, in which the best structural configuration is found by getting rid of structural members that have no contributions to the design objectives from the given initial design configuration. The second and third steps are sizing optimization. The second design step gives a set of good design solutions having higher fitness for lightweight and minimum static compliance. Finally the best solution, which has minimum dynamic compliance and weight, is extracted from the good solution set. The proposed design optimization method was successfully applied to the structural design optimization of a grinding machine. After optimization, both static and dynamic compliances are reduced more than 58.4% compared with the initial design, which was designed empirically by experienced engineers. Moreover the weight of the optimized structure are also slightly reduced than before.

Design optimization of semi-rigid space steel frames with semi-rigid bases using biogeography-based optimization and genetic algorithms

  • Shallan, Osman;Maaly, Hassan M.;Sagiroglu, Merve;Hamdy, Osman
    • Structural Engineering and Mechanics
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    • 제70권2호
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    • pp.221-231
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    • 2019
  • This paper performs for the first time a simultaneous optimization for members sections along with semi-rigid beam-to-column connections for space steel frames with fixed, semi-rigid, and hinged bases using a biogeography-based optimization algorithm (BBO) and a genetic algorithm (GA). Furthermore, a member's sections optimization for a fully fixed space frame is carried out. A real and accurate simulation of semi-rigid connection behavior is considered in this study, where the semi-rigid base connections are simulated using Kanvinde and Grilli (2012) nonlinear model, which considers deformations in different base connection components under the applied loads, while beam-to-column connections are modeled using the familiar Frye and Morris (1975) nonlinear polynomial model. Moreover, the $P-{\Delta}$ effect and geometric nonlinearity are considered. AISC-LRFD (2016) specification constraints of the stress and displacement are considered as well as section size fitting constraints. The optimization is applied to two benchmark space frame examples to inspect the effect of semi-rigidity on frame weight and drift using BBO and GA algorithms.

전역 탐색 알고리듬을 이용한 이동 무선통신 네트워크의 최적화에 대한 연구 (A Study on Mobile Wireless Communication Network Optimization Using Global Search Algorithm)

  • 김성곤
    • 한국컴퓨터정보학회논문지
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    • 제9권1호
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    • pp.87-93
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    • 2004
  • 이동 무선 통신 네트워크를 설계할 때 기지국(BTS), 기지국 콘트롤러(BSC), 이동 교환국(MSC)의 위치는 매우 중요한 파라미터들이다. 기지국의 위치를 설계할 때는 여러 가지 복잡한 변수들을 잘 조합하여 비용이 최소가 되도록 설계해야 한다 이러한 문제를 해결하는데 필요한 알고리듬이 전역 최적화 알고리듬이며, 지금까지 전역 최적화 검색 기술로는 Random Walk, Simulated Annealing, Tabu Search, Genetic Algorithm이 사용되어 왔다. 본 논문은 이동 통신 시스템의 기지국, 기지국 콘트롤러, 이동 교환국의 위치 최적화에 위의 4가지 알고리듬들을 적용하여 각 알고리듬의 결과를 비교 분석하며 알고리듬에 의한 최적화 과정을 보여준다.

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A Biologically Inspired Intelligent PID Controller Tuning for AVR Systems

  • Kim Dong-Hwa;Cho Jae-Hoon
    • International Journal of Control, Automation, and Systems
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    • 제4권5호
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    • pp.624-636
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    • 2006
  • This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.