• 제목/요약/키워드: Combined optimization strategy

검색결과 68건 처리시간 0.023초

Neighbor Generation Strategies of Local Search for Permutation-based Combinatorial Optimization

  • Hwang, Junha
    • 한국컴퓨터정보학회논문지
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    • 제26권10호
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    • pp.27-35
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    • 2021
  • 지역 탐색은 다양한 조합 최적화 문제들을 해결하기 위해 활용되어 왔다. 지역 탐색에 있어서 가장 중요한 요소 중 하나가 이웃해를 생성하는 방법이다. 본 논문에서는 순열 기반 조합 최적화를 위한 지역 탐색의 이웃해 생성 전략들을 제안하고, 순회 외판원 문제를 대상으로 각 전략들의 성능을 비교한다. 본 논문에서는 총 10가지 이웃해 생성 전략을 제안한다. 기본적으로 기존에 많이 사용했던 Swap 등 4가지 전략 이외에 Rotation 등 4가지 기법을 새롭게 제안한다. 이외에 기본 이웃해 생성 전략들을 결합하여 만든 Combined1과 Combined2가 있다. 실험은 기본적인 지역 탐색을 적용하되 이웃해 생성 전략만 변경하여 수행하였다. 실험 결과, 이웃해 생성 전략에 따라 성능 차이가 큰 것을 확인하였으며 아울러 Combined2의 성능이 가장 좋음을 확인하였다. 뿐만 아니라 Combined2는 기존의 지역 탐색 기법들보다 더 좋은 성능을 발휘함을 확인하였다.

발전력의 경쟁적 입찰전략과 전략적 보수계획에 대한 결합모형 연구 (Analysis on a Combined Model of Competitive Bidding and Strategic Maintenance Scheduling of Generating Units)

  • 이광호
    • 대한전기학회논문지:전력기술부문A
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    • 제55권9호
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    • pp.392-398
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    • 2006
  • Maintenance scheduling of generating units (MSU) has strategic dimension in an oligopolistic market. Strategic MSU of gencos can affect a market power through capacity withdrawal which is related to bidding strategy in an generation wholesale market. This paper presents a combined framework that models the interrelation between competitive bidding and strategic MSU. The combined game model is represented as some sub-optimization problems of a market operator (MO) and gencos, that should be solved through bi-level optimization scheme. The gradient method with dual variables is also adopted to calculate a Nash Equilibrium (NE) by an iterative update technique in this paper. Illustrative numerical example shows that NE of a supply function equilibrium is obtained properly by using proposed solution technique. The MSU made by MO is compared with that by each genco and that under perfect competition market.

Integrated Optimization Design of Carbon Fiber Composite Framework for Small Lightweight Space Camera

  • Yang, Shuai;Sha, Wei;Chen, Changzheng;Zhang, Xingxiang;Ren, Jianyue
    • Journal of the Optical Society of Korea
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    • 제20권3호
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    • pp.389-395
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    • 2016
  • A Carbon Fiber Composite (CFC) framework was designed for a small lightweight space camera. According to the distribution characteristics of each optical element in the optical system, CFC (M40J) was chosen to accomplish the design of the framework. TC4 embedded parts were used to solve the low accuracy of the CFC framework interface problem. An integrated optimization method and the optimization strategy which combined a genetic global optimization algorithm with a downhill simplex local optimization algorithm were adopted to optimize the structure parameters of the framework. After optimization, the total weight of the CFC framework and the TC4 embedded parts is 15.6 kg, accounting for only 18.4% that of the camera. The first order frequency of the camera reaches 104.8 Hz. Finally, a mechanical environment test was performed, and the result demonstrates that the first order frequency of the camera is 102 Hz, which is consistent with the simulation result. It further verifies the rationality and correctness of the optimization result. The integrated optimization method mentioned in this paper can be applied to the structure design of other space cameras, which can greatly improve the structure design efficiency.

Latin Hypercube Sampling Experiment와 Multiquadric Radial Basis Function을 이용한 최적화 알고리즘에 대한 연구 (Study on a Robust Optimization Algorithm Using Latin Hypercube Sampling Experiment and Multiquadric Radial Basis Function)

  • ;윤희성;고창섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.162-164
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    • 2007
  • This paper presents a "window-zoom-out" optimization strategy with relatively fewer sampling data. In this method, an optimal Latin hypercube sampling experiment based on multi-objective Pareto optimization is developed to obtain the sampling data. The response surface method with multiquadric radial basis function combined with (1+$\lambda$) evolution strategy is used to find the global optimal point. The proposed method is verified with numerical experiments.

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개선된 (1+1)Evolution Strategy를 이용한 유도전동기의 다중목적 최적 설계 (Multiobjective Optimal Design Technique for Induction Motor Using Improved (1+1)Evolution Strategy)

  • 김민규;이철균;박정태;정현교
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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    • pp.6-8
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    • 1996
  • The multiobjective optimization is presented for the optimal design of induction motors. The aim of design is to find an optimized induction motor in terms of both the efficiency and the mass. The efficiency and the mass are linearly combined using the weighting factors. Optimization process is performed by using the improved (1+1) evolution strategy (ES). ES is the algorithm that can find the global minimum. To verify the validity of the proposed method. the method is applied to a sample design.

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퍼지 결정법을 적용한 유도전동기의 최적 설계 (Application of Fuzzy Decision to Optimization of Induction Motor Design)

  • 박정태;정현교
    • 한국자기학회지
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    • 제7권2호
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    • pp.103-108
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    • 1997
  • 본 논문에서는 퍼지결정법을 적용한 유도전동기의 최적설계 방법을 제시하였다. 이 방법은 설계자의 경험, 관점, 판단을 반영할 수 있을 뿐만 아니라 다목적 최적설계에 쉽게 적용가능하다. 특성 해석방법은 등가 자기회로법이며, 설계방법은 기존 설계법 중의 하나인 D$^{2}$L 법에 퍼지 결정법과 최적화 루틴을 결합하였다. 사용한 최적화 알고리즘은 확률론적 최적화기법인 (1+1) Evolution Strategy(ES)를 이용하였다. 제안된 알고리즘은 유도전동기의 무게최소화와 동시에 주요 동작점에서의 효율, 역률을 최대화 설계하는 다중목적 최적설계에 적용되었다.

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A hybrid imperialist competitive ant colony algorithm for optimum geometry design of frame structures

  • Sheikhi, Mojtaba;Ghoddosian, Ali
    • Structural Engineering and Mechanics
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    • 제46권3호
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    • pp.403-416
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    • 2013
  • This paper describes new optimization strategy that offers significant improvements in performance over existing methods for geometry design of frame structures. In this study, an imperialist competitive algorithm (ICA) and ant colony optimization (ACO) are combined to reach to an efficient algorithm, called Imperialist Competitive Ant Colony Optimization (ICACO). The ICACO applies the ICA for global optimization and the ACO for local search. The results of optimal geometry for three benchmark examples of frame structures, demonstrate the effectiveness and robustness of the new method presented in this work. The results indicate that the new technique has a powerful search strategies due to the modifications made in search module of ICACO. Higher rate of convergence is the superiority of the presented algorithm in comparison with the conventional mathematical methods and non hybrid heuristic methods such as ICA and particle swarm optimization (PSO).

Buckling optimization of unsymmetrically laminated plates under transverse loads

  • Hu, Hsuan-Teh;Chen, Zhong-Zhi
    • Structural Engineering and Mechanics
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    • 제7권1호
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    • pp.19-33
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    • 1999
  • The critical buckling loads of unsymmetrically laminated rectangular plates with a given material system and subjected to combined lateral and inplane loads are maximized with respect to fiber orientations by using a sequential linear programming method together with a simple move-limit strategy. Significant influence of plate aspect ratios, central circular cutouts, lateral loads and end conditions on the optimal fiber orientations and the associated optimal buckling loads of unsymmetrically laminated plates has been shown through this investigation.

A CLASS OF NONMONOTONE SPECTRAL MEMORY GRADIENT METHOD

  • Yu, Zhensheng;Zang, Jinsong;Liu, Jingzhao
    • 대한수학회지
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    • 제47권1호
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    • pp.63-70
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    • 2010
  • In this paper, we develop a nonmonotone spectral memory gradient method for unconstrained optimization, where the spectral stepsize and a class of memory gradient direction are combined efficiently. The global convergence is obtained by using a nonmonotone line search strategy and the numerical tests are also given to show the efficiency of the proposed algorithm.

실시간 계산에서 수령속도 개선을 위한 SDS 알고리즘의 개발 (A Development of SDS Algorithm for the Improvement of Convergence Simulation)

  • 이영진;장용훈;이권순
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 하계학술대회 논문집 B
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    • pp.699-701
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    • 1997
  • The simulated annealing(SA) algorithm is a stochastic strategy for search of the ground state and a powerful tool for optimization, based on the annealing process used for the crystallization in physical systems. It's main disadvantage is the long convergence time. Therefore, this paper proposes a stochastic algorithm combined with conventional deterministic optimization method to reduce the computation time, which is called SDS(Stochastic-Deterministic-Stochastic) method.

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