• 제목/요약/키워드: approximate algorithm

검색결과 698건 처리시간 0.026초

A MODIFIED BFGS BUNDLE ALGORITHM BASED ON APPROXIMATE SUBGRADIENTS

  • Guo, Qiang;Liu, Jian-Guo
    • Journal of applied mathematics & informatics
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    • 제28권5_6호
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    • pp.1239-1248
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    • 2010
  • In this paper, an implementable BFGS bundle algorithm for solving a nonsmooth convex optimization problem is presented. The typical method minimizes an approximate Moreau-Yosida regularization using a BFGS algorithm with inexact function and the approximate gradient values which are generated by a finite inner bundle algorithm. The approximate subgradient of the objective function is used in the algorithm, which can make the algorithm easier to implement. The convergence property of the algorithm is proved under some additional assumptions.

AN APPROXIMATE GREEDY ALGORITHM FOR TAGSNP SELECTION USING LINKAGE DISEQUILIBRIUM CRITERIA

  • Wang, Ying;Feng, Enmin;Wang, Ruisheng
    • Journal of applied mathematics & informatics
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    • 제26권3_4호
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    • pp.493-500
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    • 2008
  • In this paper, we first construct a mathematical model for tagSNP selection based on LD measure $r^2$, then aiming at this kind of model, we develop an efficient algorithm, which is called approximate greedy algorithm. This algorithm is able to make up the disadvantage of the greedy algorithm for tagSNP selection. The key improvement of our approximate algorithm over greedy algorithm lies in that it adds local replacement(or local search) into the greedy search, tagSNP is replaced with the other SNP having greater similarity degree with it, and the local replacement is performed several times for a tagSNP so that it can improve the tagSNP set of the local precinct, thereby improve tagSNP set of whole precinct. The computational results prove that our approximate greedy algorithm can always find more efficient solutions than greedy algorithm, and improve the tagSNP set of whole precinct indeed.

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An Approximate Euclidean Distance Calculation for Fast VQ Encoding

  • Baek, Seong-Joon;Kim, Jin-Young;Kang, Sang-Ki
    • 음성과학
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    • 제11권2호
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    • pp.211-216
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    • 2004
  • In this paper, we present a fast encoding algorithm for vector quantization with an approximate Euclidean distance calculation. An approximation is performed by converting floating point to the near integer. An inequality between the approximate Euclidean distance and the nearest distance is developed to avoid unnecessary distance calculations. Since the proposed algorithm rejects those codewords that are impossible to be the nearest codeword, it produces the same output as conventional full search algorithm.

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응답량 재사용을 통한 순차 근사최적설계 (A Sequential Approximate Optimization Technique Using the Previous Response Values)

  • 황태경;최은호;임오강
    • 대한기계학회논문집A
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    • 제29권1호
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    • pp.45-52
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    • 2005
  • A general approximate optimization technique by sequential design domain(SDD) did not save response values for getting an approximate function in each step. It has a disadvantage at aspect of an expense. In this paper, previous response values are recycled for constructing an approximate function. For this reason, approximation function is more accurate. Accordingly, even if we did not determine move limit, a system is converged to the optimal design. Size and shape optimization using approximate optimization technique is carried out with SDD. Algorithm executing Pro/Engineer and ANSYS are automatically adopted in the approximate optimization program by SDD. Convergence criterion is defined such that optimal point must be located within SDD during the three steps. The PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve approximate optimization problems. This algorithm uses the second-order information in the direction finding problem and uses the active set strategy.

A SPARSE APPROXIMATE INVERSE PRECONDITIONER FOR NONSYMMETRIC POSITIVE DEFINITE MATRICES

  • Salkuyeh, Davod Khojasteh
    • Journal of applied mathematics & informatics
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    • 제28권5_6호
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    • pp.1131-1141
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    • 2010
  • We develop an algorithm for computing a sparse approximate inverse for a nonsymmetric positive definite matrix based upon the FFAPINV algorithm. The sparse approximate inverse is computed in the factored form and used to work with some Krylov subspace methods. The preconditioner is breakdown free and, when used in conjunction with Krylov-subspace-based iterative solvers such as the GMRES algorithm, results in reliable solvers. Some numerical experiments are given to show the efficiency of the preconditioner.

재해석 기법을 이용한 강상자형교의 최적설계 (Optimization of Steel Box Girder Bridges using Approximate Reanalysis Technique)

  • 민대홍;윤우현;정지승;양성돈
    • 한국안전학회지
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    • 제26권4호
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    • pp.80-86
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    • 2011
  • Structural optimization algorithm of steel box girder bridges using improved higher-order approximate reanalysis technique is proposed in this paper. The proposed approximation method is a generalization of the convex approximation method. The order of the approximate reanalysis for each function is analytically adjusted in the optimization process. This self-adjusted capability makes the approximate structural analysis values conservative enough to maintain the optimum design point of the approximate problem. The efficiency of proposed optimazation algorithm, compared with conventional algorithm, is successfully demonstrated in the steel box girder bridges. The efficiency and robustness of proposed algorithm is also demonstrated in practical steel box girder bridges.

내용 기반 멀티미디어 정보 검색을 위한 근사 k-최근접 데이타 탐색 알고리즘 (An Approximate k-Nearest Neighbor Search Algorithm for Content- Based Multimedia Information Retrieval)

  • 송광택;장재우
    • 한국정보과학회논문지:데이타베이스
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    • 제27권2호
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    • pp.199-208
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    • 2000
  • 내용 기반 멀티미디어 정보 검색에서 유사성에 기반한 k-최근접 데이타 탐색 질의는 매우 중요한 질의이다 일반적으로 멀티미디어 데이타는 고차원 특정 벡터로 표현되기 때문에 기존의 k-최근접 탐색 알고리즘은 멀티미디어 정보 검색에 효율적이지 못하다. 따라서 이러한 응용을 위해서는 다소 근사적 검색 결과를 가져오더라도 빠른 검색 성능을 제공하는 근사 k-최근접 탐색 알고리즘이 요구된다. 이를 위해 본 논문에서는 고차원 데이타를 위한 새로운 근사 k-최근접 탐색 알고리즘을 제안한다. 아울러, 제안하는 근사 k-최근접 탐색 알고리즘을 기존의 알고리즘과 검색 성능변에서 성능 평가를 수행한다. 성능 평가 결과, 기존 알고리즘의 검색 성능을 크게 개선할 수 있었다.

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노이즈 필터링을 적용한 반응표면 기반 순차적 근사 최적화 (Sequential Approximate Optimization Based on a Pure Quadratic Response Surface Method with Noise Filtering)

  • 이용빈;이호준;김민수;최동훈
    • 대한기계학회논문집A
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    • 제29권6호
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    • pp.842-851
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    • 2005
  • In this paper, a new method for constrained optimization of noisy functions is proposed. In approximate optimization using response surface methods, if constraints have severe noise, the approximate feasible region defined by approximate constraints is apt to include some of the infeasible region defined by actual constraints. This can cause the approximate optimum to converge into the infeasible region. In the proposed method, the approximate optimization is performed with the approximate constraints shifted by their deviations, which are calculated using a diagonal quadratic response surface method. This can prevent the approximate optimum from converging into the infeasible region. To fit the objective and constraints into diagonal quadratic models, we select the center and 4 additional points along each axis of design variables as experimental points. The deviation of each function is calculated using the differences between the real and approximate function values at the experimental points. A sequential approximate optimization technique based on the trust region algorithm is adopted to manage approximate models. The proposed approach is validated by solving some design problems. The results of the problems show the effectiveness of the proposed method.

APPROXIMATE PROJECTION ALGORITHMS FOR SOLVING EQUILIBRIUM AND MULTIVALUED VARIATIONAL INEQUALITY PROBLEMS IN HILBERT SPACE

  • Khoa, Nguyen Minh;Thang, Tran Van
    • 대한수학회보
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    • 제59권4호
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    • pp.1019-1044
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    • 2022
  • In this paper, we propose new algorithms for solving equilibrium and multivalued variational inequality problems in a real Hilbert space. The first algorithm for equilibrium problems uses only one approximate projection at each iteration to generate an iteration sequence converging strongly to a solution of the problem underlining the bifunction is pseudomonotone. On the basis of the proposed algorithm for the equilibrium problems, we introduce a new algorithm for solving multivalued variational inequality problems. Some fundamental experiments are given to illustrate our algorithms as well as to compare them with other algorithms.

GENIIS, a New Hybrid Algorithm for Solving the Mixed Chinese Postman Problem

  • 최명길;응우엔만탕;황원주
    • 한국정보시스템학회지:정보시스템연구
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    • 제17권3호
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    • pp.39-58
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    • 2008
  • Mixed Chinese Postman Problem (MCPP) is a practical generalization of the classical Chinese Postman Problem (CPP) and it could be applied in many real world. Although MCPP is useful in terms of reality, MCPP has been proved to be a NP-complete problem. To find optimal solutions efficiently in MCPP, we can reduce searching space to be small effective searching space containing optimal solutions. We propose GENIIS methodology, which is a kind of hybrid algorithm combines the approximate algorithms and genetic algorithm. To get good solutions in the effective searching space, GENIIS uses approximate algorithm and genetic algorithm. This paper validates the usefulness of the proposed approach in a simulation. The results of our paper could be utilized to increase the efficiencies of network and transportation in business.