• Title, Summary, Keyword: discrete optimization

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Discrete Structural Design of Reinforced Concrete Frame by Genetic Algorithm (유전알고리즘에 의한 철근콘크리트 골조의 이산형 구조설계)

  • Ahn, Jeehyun;Lee, Chadon
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • pp.127-134
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    • 1999
  • An optimization algorithm based on Genetic Algorithm(GA) is developed for discrete optimization of reinforced concrete plane frame by constructing databases. Under multiple loading conditions, discrete optimum sets of reinforcements for both negative and positive moments in beams, their dimensions, column reinforcement, and their column dimensions are found. Construction practice is also implemented by linking columns and beams by group ‘Connectivity’between columns located in the same column line is also considered. It is shown that the developed genetic algorithm was able to reach optimum design for reinforced concrete plane frame construction practice.

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Global Optimization Using a Sequential Algorithm with Orthogonal Arrays in Discrete Space (이산공간에서 순차적 알고리듬(SOA)을 이용한 전역최적화)

  • Cho Bum-Sang;Yi Jeong-Wook;Park Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.10
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    • pp.1369-1376
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    • 2005
  • In structural design, the design variables are frequently selected from certain discrete values. Various optimization algorithms have been developed fDr discrete design. It is well known that many function evaluations are needed in such optimization. Recently, sequential algorithm with orthogonal arrays (SOA), which is a search algorithm for a local minimum in a discrete space, has been developed. It considerably reduces the number of function evaluations. However, it only finds a local minimum and the final solution depends on the initial values of the design variables. A new algorithm is proposed to adopt a genetic algorithm (GA) in SOA. The GA can find a solution in a global sense. The solution from the GA is used as the initial design of SOA. A sequential usage of the GA and SOA is carried out in an iterative manner until the convergence criteria are satisfied. The performance of the algorithm is evaluated by various examples.

Rule-based Hybrid Discretization of Discrete Particle Swarm Optimization for Optimal PV System Allocation (PV 시스템의 최적 배치 문제를 위한 이산 PSO에서의 규칙 기반 하이브리드 이산화)

  • Song, Hwa-Chang;Ko, Jae-Hwan;Choi, Byoung-Wook
    • Journal of Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.792-797
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    • 2011
  • This paper discusses the application of a hybrid discretiziation method for the discretization procedure that needs to be included in discrete particle swarm optimization (DPSO) for the problem of allocating PV (photovoltaic) systems onto distribution power systems. For this purpose, this paper proposes a rule-based expert system considering the objective function value and its optimizing speed as the input parameters and applied it to the PV allocation problem including discrete decision variables. For multi-level discretization, this paper adopts a hybrid method combined with a simple rounding and sigmoid funtion based 3-step and 5-step quantization methods, and the application of the rule based expert system proposing the adequate discretization method at each PSO iteration so that the DPSO with the hybrid discretization can provide better performance than the previous DPSO.

Reliability-based Design Optimization for Lower Control Arm using Limited Discrete Information (제한된 이산정보를 이용한 로어컨트롤암의 신뢰성 기반 최적설계)

  • Jang, Junyong;Na, Jongho;Lim, Woochul;Park, Sanghyun;Choi, Sungsik;Kim, Jungho;Kim, Yongsuk;Lee, Tae Hee
    • Transactions of the Korean Society of Automotive Engineers
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    • v.22 no.2
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    • pp.100-106
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    • 2014
  • Lower control arm (LCA) is a part of chassis in automotive. Performances of LCA such as stiffness, durability and permanent displacement must be considered in design optimization. However it is hard to consider different performances at once in optimization because these are measured by different commercial tools like Radioss, Abaqus, etc. In this paper, firstly, we construct the integrated design automation system for LCA based on Matlab including Hypermesh, Radioss and Abaqus. Secondly, Akaike information criterion (AIC) is used for assessment of reliability of LCA. It can find the best estimated distribution of performance from limited and discrete stochastic information and then obtains the reliability from the distribution. Finally, we consider tolerances of design variables and variation of elastic modulus and achieve the target reliability by carrying out reliability-based design optimization (RBDO) with the integrated system.

Optimi Design for R.C. Beam with Discrete Variables (이산형 설계변수를 갖는 철그콘크리트보의 최적설계)

  • 구봉근;한상훈;김홍룡
    • Magazine of the Korea Concrete Institute
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    • v.5 no.4
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    • pp.167-178
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    • 1993
  • The objective of this paper is to look into the possibility of the detailed and practical optimum design of rt:inforced concrete beam using methods oi discrete mathematical programming. In this discrete optimum formulation, the design variables are the overall depth, width and effective depth of members, and area of longitudinal reinforcement. In addition, the details such as the amount of web reinforcement and cutoff points of longitudinal reinforcement are also considered as variables. Total cost has been used as the objective function. The constraints include the code requirments such as flexural strength, shear strength, ductility, serviceability, concrete cover. spacing, web reinforcement, and development length and cutoff points of longitudinal renforcement. An optimization algorithm is presented for effective optimum design of R.C. beam with discrete de sign variables. First, the continuous variable optimization can be achieved by Feasible Direction Method. Using the results obtained from the continuous variable optimization, a branch and bound method is used to obtained the discrete design values. The proposed algorithm is applied to test problem for reliability, and the results are compared with those of graphical method and rounded-up method. And a simply supported R.C. beam and a two-span continuous R.C. beam are presented as numerical examples for effectiveness and applicability. It is considered that the presented algorithm can be effectively applied to the discrete optimum design of R.C. beams.

A Study of Frequency Mixing Approaches for Eddy Current Testing of Steam Generator Tubes

  • Jung, Hee-Jun;Song, Sung-Jin;Kim, Chang-Hwan;Kim, Dea-Kwang
    • Journal of the Korean Society for Nondestructive Testing
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    • v.29 no.6
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    • pp.579-585
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    • 2009
  • The multifrequency eddy current testing(ECT) have been proposed various frequency mixing algorithms. In this study, we compare these approaches to frequency mixing of ECT signals from steam generator tubes; time-domain optimization, discrete cosine transform-domain optimization. Specifically, in this study, two different frequency mixing algorithms, a time-domain optimization method and a discrete cosine transform(DCT) optimization method, are investigated using the experimental signals captured from the ASME standard tube. The DCT domain optimization method is computationally fast but produces larger amount of residue.

Discrete Optimum Design of Ship Structures by Genetic Algorithm (유전적 알고리즘에 의한 선체 구조물의 이산적 최적설계)

  • Y.S. Yang;G.H. Kim;W.S. Ruy
    • Journal of the Society of Naval Architects of Korea
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    • v.31 no.4
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    • pp.147-156
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    • 1994
  • Though optimization method had been used for long time for the optimal design of ship structure, design variables in the most cases were assumed to be continuous real values or it was not easy to solve the mixed integer optimum design problems using the conventional optimization methods. Thus, it was often tried to use various initial starting points to locate the best optimum paint and to use special method such as branch and bound method to handle the discrete design variables in the optimization problems. Sometimes it had succeed, but the essential problems for dealing with the local optimum and discrete design variables was left unsolved. Hence, in this paper, Genetic Algorithms adopting the biological evolution process is applied to the ship structural design problem where the integer values for the number of stiffen design variables or the discrete values for the plate thickness variables would be more preferable in order to find out their effects on the final optimum design. Through the numerical result comparisons, it was found that Genetic Algorithm could always yield the global optimum for the discrete and mixed integer structural optimization problem cases even though it takes more time than other methods.

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Summarized IDA curves by the wavelet transform and bees optimization algorithm

  • Shahryari, Homayoon;Karami, M. Reza;Chiniforush, Alireza A.
    • Earthquakes and Structures
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    • v.16 no.2
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    • pp.165-175
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    • 2019
  • Incremental dynamic analysis (IDA), as an accurate method to evaluate the parameters of structural performance levels, requires many non-linear time history analyses, using a set of ground motion records which are scaled to different intensity levels. Therefore, this method is very computationally demanding. In this study, a new method is presented to estimate the summarized (16%, 50%, and 84% fractiles) IDA curves of a first-mode dominated structure using discrete wavelet transform and bees optimization algorithm. This method reduces the number of required ground motion records for the prediction of the summarized IDA curves. At first, a subset of first list ground motion records is decomposed by means of discrete wavelet transform which have a low dispersion estimating the summarized IDA curves of equivalent SDOF system of the main structure. Then, the bees algorithm optimizes a series of factors for each level of detail coefficients in discrete wavelet transform. The applied factors change the frequency content of original ground motion records which the generated ground motions records can be utilized to reliably estimate the summarized IDA curves of the main structure. At the end, to evaluate the efficiency of the proposed method, the seismic behavior of a typical 3-story special steel moment frame, subjected to a set of twenty ground motion records is compared with this method.

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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    • 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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Discrete approaches in evolution strategies based optimum design of steel frames

  • Hasancebi, O.
    • Structural Engineering and Mechanics
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    • v.26 no.2
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    • pp.191-210
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    • 2007
  • The three different approaches (reformulations) of evolution strategies (ESs) have been proposed in the literature as extensions of the technique for solving discrete problems. This study implements an extensive research on application, evaluation and comparison of them in discrete optimum design of steel frames. A unified formulation is first developed to explain these approaches, so that differences and similarities between their inherent search mechanisms can clearly be identified. Two examples from practical design of steel frames are studied next to measure their performances in locating the optimum. Extensive numerical experimentations are performed in both examples to facilitate a statistical analysis of their convergence characteristics. The results obtained are presented in the histograms demonstrating the distribution of the best designs located by each approach. In addition, an average improvement of the best design during the course of evolution is plotted in each case to compare their relative convergence rates.