• Title/Summary/Keyword: meta heuristic

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Application of Candidate Order Approach for Solving Job Sequencing Problem with Finish Date Constraint (완료 시간 제약이 있는 작업 순서 결정 문제 풀이를 위한 후보 순위 접근법 응용)

  • Kim, Jun Woo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2018.07a
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    • pp.421-422
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    • 2018
  • 작업 순서 결정 문제의 목표는 다양한 작업들에 대한 최적의 처리 순서를 결정하여 총 처리시간이나 납기 지연과 관련된 지표들을 최소화하는 것이다. 나아가, 실제 생산 현장에서는 작업 처리 순서를 결정할 때, 긴급도나 고객과의 관계 등과 같은 요인을 고려하여 일부 작업들을 특정 시간 내에 완료해야 할 수 있으며, 이 같은 제약 조건을 완료 시간 제약이라 한다. 본 논문에서는 완료 시간 제약을 갖는 작업 순서 결정 문제의 개념과 특성에 대해 살펴보고, 이러한 문제를 풀이하기 위한 알고리즘 개발에 후보 순위 접근법을 적용할 것을 제안한다.

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Machine-Part Cell Formation based on Kohonen화s Self Organizing Feature Map (Kohonen 자기조직화 map 에 기반한 기계-부품군 형성)

  • ;;山川 烈
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.315-318
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    • 1996
  • The machine-part cell formation means the grouping of similar parts and similar machines into families in order to minimize bottleneck machines, bottleneck parts, and inter-cell part movements in cellular manufacturing systems and flexible manufacturing systems. The cell formation problem is knows as a kind of NP complete problems. This paper briefly introduces the cell-formation problem and proposes a cell formation method based on the Kohonen's self-organizing feature map which is a neural network model. It also shows some experiment results using the proposed method. The proposed method can be easily applied to the cell formation problem compared to other meta-heuristic based methods. In addition, it can be used to solve large-scale cell formation problems.

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A Consideration of Automatic module Placement for VLSI Layout Design

  • T.Kutsuwa;Na, M.koshi;K.harashima;K.Kobori;K.Oba
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.375-378
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    • 2000
  • This paper discusses on application of meta-heuristic algorithms such as the genetic algorithm (GA) and the simulated annealing (SA) to the LSI module placement. We propose useful crossover method for improving of searching capability in genetic algorithm. By using our proposed crossover method, we have been able to keep good schemata in the chromosome and the variety of the solution. From the experimental results, we have obtained better result than the simulated annealing method by starting from the initial placement of the min-cut method.

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Harmony search algorithm for optimum design of steel frame structures: A comparative study with other optimization methods

  • Degertekin, S.O.
    • Structural Engineering and Mechanics
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    • v.29 no.4
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    • pp.391-410
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    • 2008
  • In this article, a harmony search algorithm is presented for optimum design of steel frame structures. Harmony search is a meta-heuristic search method which has been developed recently. It is based on the analogy between the performance process of natural music and searching for solutions of optimization problems. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) and AISC Allowable Stress Design (ASD) specifications, maximum (lateral displacement) and interstorey drift constraints, and also size constraint for columns were imposed on frames. The results of harmony search algorithm were compared to those of the other optimization algorithms such as genetic algorithm, optimality criterion and simulated annealing for two planar and two space frame structures taken from the literature. The comparisons showed that the harmony search algorithm yielded lighter designs for the design examples presented.

Reduced record method for efficient time history dynamic analysis and optimal design

  • Kaveh, A.;Aghakouchak, A.A.;Zakian, P.
    • Earthquakes and Structures
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    • v.8 no.3
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    • pp.639-663
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    • 2015
  • Time history dynamic structural analysis is a time consuming procedure when used for large-scale structures or iterative analysis in structural optimization. This article proposes a new methodology for approximate prediction of extremum point of the response history via wavelets. The method changes original record into a reduced record, decreasing the computational time of the analysis. This reduced record can be utilized in iterative structural dynamic analysis of optimization and hence significantly reduces the overall computational effort. Design examples are included to demonstrate the capability and efficiency of the Reduced Record Method (RRM) when utilized in optimal design of frame structures using meta-heuristic algorithms.

Optimum design of geometrically non-linear steel frames using artificial bee colony algorithm

  • Degertekin, S.O.
    • Steel and Composite Structures
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    • v.12 no.6
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    • pp.505-522
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    • 2012
  • An artificial bee colony (ABC) algorithm is developed for the optimum design of geometrically non-linear steel frames. The ABC is a new swarm intelligence method which simulates the intelligent foraging behaviour of honeybee swarm for solving the optimization problems. Minimum weight design of steel frames is aimed under the strength, displacement and size constraints. The geometric non-linearity of the frame members is taken into account in the optimum design algorithm. The performance of the ABC algorithm is tested on three steel frames taken from literature. The results obtained from the design examples demonstrate that the ABC algorithm could find better designs than other meta-heuristic optimization algorithms in shorter time.

Edge Detection Using an Ant System Algorithm (개미 시스템 알고리듬을 이용한 윤곽선 검출)

  • 이성열;이창훈
    • Journal of Korea Society of Industrial Information Systems
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    • v.8 no.4
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    • pp.38-45
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    • 2003
  • This paper presents a meta-heuristic solution technique, Ant System (AS)algerian to solve edge detection problem. We define the quality of edge in terms of dissimilarity, continuity, thickness and length. We cast edge detection as a problem in cost minimization. This is achieved by the formulation of a cost function that inversely evaluates the quality of edge configuration. Twelve windows for enhancing dissimilarity regions based on the valid edge structures are used. The AS algorithm finds the optimal set of edge pixels based on the cost function. The experimental results show that the properly reduced set of edge pixels could be found regardless how complicated the image is.

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Game-Scheduling by Mathematical Programming and Expert System (수리계획법과 전문가 시스템을 이용한 경기 일정 작성)

  • Jo, Hyeon-Bo;Park, Sun-Dal
    • Journal of Korean Institute of Industrial Engineers
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    • v.14 no.2
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    • pp.53-61
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    • 1988
  • Games such as baseball, soccer are scheduled by a given game type such as tournament, league or their mixed form. The objective of this paper is to find an efficient game-scheduling method with respect to traveling distance, break-time and other conditions. In this paper we first present two models which minimize traveling distance. The first model that a match is played once each other is solved by a heuristic method. In the second model that a match is played more than once, teams are paired by a modified 0 - 1 programming, and the pairs are rearranged in order to generate a number of workable schedules. Then Expert Systems is applied to solve breake-time and other conditions. In order to represent expertise's knowledge effectively, we present a new design of knowledge-base and data-base, inference engine including many rules and meta-rules which controls the global system. In knowledge-base, binary relation among various attributes is used to ease not only knowledge acquisition but also system execution.

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Analysis of Evolutionary Optimization Methods for CNN Structures (CNN 구조의 진화 최적화 방식 분석)

  • Seo, Kisung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.6
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    • pp.767-772
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    • 2018
  • Recently, some meta-heuristic algorithms, such as GA(Genetic Algorithm) and GP(Genetic Programming), have been used to optimize CNN(Convolutional Neural Network). The CNN, which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures still requires expert knowledge and a lot of trial and error. In this paper, the recent attempts to automatically construct CNN architectures are investigated and analyzed. First, two GA based methods are summarized. One is the optimization of CNN structures with the number and size of filters, connection between consecutive layers, and activation functions of each layer. The other is an new encoding method to represent complex convolutional layers in a fixed-length binary string, Second, CGP(Cartesian Genetic Programming) based method is surveyed for CNN structure optimization with highly functional modules, such as convolutional blocks and tensor concatenation, as the node functions in CGP. The comparison for three approaches is analysed and the outlook for the potential next steps is suggested.

Optimal Operation Method of Microgrid System Using DS Algorithm (DS 알고리즘을 이용한 마이크로 그리드 최적운영기법)

  • Park, Si-Na;Rhee, Sang-Bong
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.29 no.5
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    • pp.34-40
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    • 2015
  • This paper presents an application of Differential Search (DS) meta-heuristic optimization algorithm for optimal operation of micro grid system. DS algorithm has the benefit of high convergence rate and precision compared to other optimization methods. The micro grid system consists of a wind turbine, a diesel generator, and a fuel cell. The simulation is applied to micro grid system only. The wind turbine generator is modeled by considering the characteristics of variable output. One day load data which is divided every 20 minute and wind resource for wind turbine generator are used for the study. The method using the proposed DS algorithm is easy to implement, and the results of the convergence performance are better than other optimization algorithms.