• Title/Summary/Keyword: discrete variables

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Complex Discrete Systems Graph Simulation

  • Kadirova, Delovar;Kadirova, Aziza
    • Journal of Multimedia Information System
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    • v.2 no.3
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    • pp.263-274
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    • 2015
  • The subject of this work is the complex discrete systems simulation special features with the aid of dynamic graph models. The proposed simulation technique allows to determine the ways for tasks solutions in terms of discrete systems analysis and synthesis of various complication: one-dimensional and multidimensional, steady and unstable, with the pulse elements abnormal operating mode and others. Often complex control systems analysis and synthesis task solutions, via classical approach comes out to be insolvent, because of the computational problems. The application of graph models allows to perform clear and strict characterization and computer procedures automation. The optimal controls synthesis algorithm presented in this paper, transferring the discrete system from target initial state to target final state within the minimum time, allows to consider the zero initial conditions systems, with the initial potential energy, with the control actions limitations and complex pulse elements operating mode.

Discrete Optimization of Plane Frame Structures Using Genetic Algorithms (유전자 알고리즘을 이용한 뼈대구조물의 이산최적화)

  • 김봉익;권중현
    • Journal of Ocean Engineering and Technology
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    • v.16 no.4
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    • pp.25-31
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    • 2002
  • This paper is to find optimum design of plane framed structures with discrete variables. Global search algorithms for this problem are Genetic Algorithms(GAs), Simulated Annealing(SA) and Shuffled Complex Evolution(SCE), and hybrid methods (GAs-SA, GAs-SCE). GAs and SA are heuristic search algorithms and effective tools which is finding global solution for discrete optimization. In particular, GAs is known as the search method to find global optimum or near global optimum. In this paper, reinforced concrete plane frames with rectangular section and steel plane frames with W-sections are used for the design of discrete optimization. These structures are designed for stress constraints. The robust and effectiveness of Genetic Algorithms are demonstrated through several examples.

Approximate Optimization with Discrete Variables of Fire Resistance Design of A60 Class Bulkhead Penetration Piece Based on Multi-island Genetic Algorithm (다중 섬 유전자 알고리즘 기반 A60 급 격벽 관통 관의 방화설계에 대한 이산변수 근사최적화)

  • Park, Woo-Chang;Song, Chang Yong
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.6
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    • pp.33-43
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    • 2021
  • A60 class bulkhead penetration piece is a fire resistance system installed on a bulkhead compartment to protect lives and to prevent flame diffusion in a fire accident on a ship and offshore plant. This study focuses on the approximate optimization of the fire resistance design of the A60 class bulkhead penetration piece using a multi-island genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class bulkhead penetration piece. For approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were considered discrete design variables; moreover, temperature, cost, and productivity were considered constraint functions. The approximate optimum design problem based on the meta-model was formulated by determining the discrete design variables by minimizing the weight of the A60 class bulkhead penetration piece subject to the constraint functions. The meta-models used for the approximate optimization were the Kriging model, response surface method, and radial basis function-based neural network. The results from the approximate optimization were compared to the actual results of the analysis to determine approximate accuracy. We conclude that the radial basis function-based neural network among the meta-models used in the approximate optimization generates the most accurate optimum design results for the fire resistance design of the A60 class bulkhead penetration piece.

Discrete Optimum Design of Reinforced Concrete Beams using Genetic Algorithm (유전알고리즘을 이용한 철근콘크리트보의 이산최적설계)

  • Hong, Ki-Nam;Han, Sang-Hoon
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.9 no.1
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    • pp.259-269
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    • 2005
  • This paper describes the application of genetic algorithm for the discrete optimum design of reinforced concrete continuous beams. The objective is to minimize the total cost of reinforced concrete beams including the costs of concrete, form work, main reinforcement and stirrup. The flexural and shear strength, deflection, crack, spacing of reinforcement, concrete cover, upper-lower bounds on main reinforcement, beam width-depth ratio and anchorage for main reinforcement are considered as the constraints. The width and effective depth of beam and steel area are taken as design variables, and those are selected among the discrete design space which is composed with dimensions and steel area being used from in practice. Optimum result obtained from GA is compared with other literature to verify the validity of GA. To show the applicability and efficiency of GA, it is applied to three and five span reinforced concrete beams satisfying with the Korean standard specifications.

Oscillation Phenomena of the discrete Optimum Solutions and control (불연속 최적해의 흔들림 현상과 제어에 관한 연구)

  • Choi, Chang-Koon;Jin, Ho-Kyun;Kim, Jong-Soo;Lee, Hwan-Woo
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1994.10a
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    • pp.9-16
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    • 1994
  • In the discrete optimum design, occasionally, the solutions oscillate between the feasible and the infeasible resions during the series of redesigns of members with discrete sections. This phenomenon may be caused inherently by the discontinuity of variables of commercially available sections in the database. In this paper, in-depth investigation into the oscillation in the discrete optimization and its control has been conducted. When the structure is optimized through element optimization, the oscillation can be divided into two categories, local and global oscillations. An algorithm which controls these phenomena is suggested and numerical examples demonstrate the oscillation in optimum solutions and the effectiveness of the control strategy suggested here.

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Simulation Study of Discrete Event Systems using Fast Approximation Method of Single Run and Optimization Method of Multiple Run (단일 실행의 빠른 근사해 기법과 반복 실행의 최적화 기법을 이용한 이산형 시스템의 시뮬레이션 연구)

  • Park, Kyoung Jong;Lee, Young Hae
    • Journal of Korean Institute of Industrial Engineers
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    • v.32 no.1
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    • pp.9-17
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    • 2006
  • This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event simulation. The developed algorithm uses the configuration algorithm that can change decision variables and the stopping algorithm that can end simulation in order to satisfy the given objective value during single run. It tries to estimate an auto-regressive model for evaluating correctly the objective function obtained by a small amount of output data. We apply the proposed algorithm to M/M/s model, (s, S) inventory model, and known-function problem. The proposed algorithm can't always guarantee the optimal solution but the method gives an approximate feasible solution in a relatively short time period. We, therefore, show the proposed algorithm can be used as an initial feasible solution of existing optimization methods that need multiple simulation run to search an optimal solution.

VUS and HUM Represented with Mann-Whitney Statistic

  • Hong, Chong Sun;Cho, Min Ho
    • Communications for Statistical Applications and Methods
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    • v.22 no.3
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    • pp.223-232
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    • 2015
  • The area under the ROC curve (AUC), the volume under the ROC surface (VUS) and the hypervolume under the ROC manifold (HUM) are defined and interpreted with probability that measures the discriminant power of classification models. AUC, VUS and HUM are expressed with the summation and integration notations for discrete and continuous random variables, respectively. AUC for discrete two random samples is represented as the nonparametric Mann-Whitney statistic. In this work, we define conditional Mann-Whitney statistics to compare more than two discrete random samples as well as propose that VUS and HUM are represented as functions of the conditional Mann-Whitney statistics. Three and four discrete random samples with some tie values are generated. Values of VUS and HUM are obtained using the proposed statistic. The values of VUS and HUM are identical with those obtained by definition; therefore, both VUS and HUM could be represented with conditional Mann-Whitney statistics proposed in this paper.

Development of Continuous/Discrete Mixed $H_2$/H$\infty$ Filtering Design Algorithms for Time Delay Systems

  • Kim, Jong-Hae
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.3
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    • pp.163-168
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    • 2000
  • The problems of mixed $H_2/H_{\infty}$ filtering design fer continuous and discrete time linear systems with time delay are investigated. The main purpose is to design a stable mixed $H_2/H_{\infty}$ filter which minimizes the H$_2$Performance measure satisfying a prescribed H$_{\infty}$ norm bound on the closed loop system in continuous-time case and discrete-time case, respectively. The sufficient conditions of existence of filter, the mixed $H_2/H_{\infty}$ filter design method, and the upper bound of performance measure are proposed by LMI(linear matrix inequality) techniques in terms of all finding variables. Also, we present optimization problems in order to get the optimal mixed $H_2/H_{\infty}$ filter in continuous and discrete time case, respectively.

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Size and Shape Discrete Optimum Design of Planar and Spacial Steel Structures Using Fuzzy-Genetic Algorithms (퍼지-유전자알고리즘에 의한 평면 및 입체 강구조물의 단면/형상 이산화 최적설계)

  • Park, Choon-Wook;Yuh, Baeg-Youh;Kim, Su-Won
    • Proceeding of KASS Symposium
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    • 2005.05a
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    • pp.236-245
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    • 2005
  • This paper was developed the discrete optimum design program by the refined fuzzy-genetic algorithms based on the genetic algorithms and fuzzy theory. The optimum design of this paper can perform both size and shape optimum design for planar and spacial steel structures. In this paper, the objective function is the weight of steel structures and the constraints are the design limits defined by design and buckling strengths, displacements and thicknesses. The design variables are dimensions and coordinates of steel sections. Design examples are given to show the applicability of the discrete optimum design program of this paper.

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Optimum Design of Greenhouse Structures Using Continuous and Discrete Optimum Algorithms (연속 및 이산화 최적알고리즘에 의한 단동온실구조의 최적설계)

  • Park, Choon-Wook;Lee, Suk-Gun;Lee, Jong-Won;Lee, Hyun-Woo
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2005.10a
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    • pp.199-206
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    • 2005
  • In paper the discrete optimum design program was developed using the continuous and discrete optimum algorithms based on the SUMT and genetic algorithms. In this paper, the objective function is the weight of structures and the constraints are limits state design limits method. The design variables are diameter and thick of steel pipe. Design examples are given to show the applicability of the optimum design using the continuous and discrete optimum algorithms based on the SUMT and genetic algorithms of this study.

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