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parallel genetic algorithm with parameter adaptation

INFORMATION PROCESSING LETTERS 2002年第1期82卷 47-54页

作者： Tongchim, S Chongstitvatana, P Chulalongkorn Univ Dept Comp Engn Bangkok 10330 Thailand

This paper presents an adaptive algorithm that can adjust parameters of a genetic algorithm according to the observed performance. The parameter adaptation occurs in parallel to the running of the genetic algorithm. The proposed method is compared with the algorithms that use random parameter sets and a standard parameter set. The experimental results show that the proposed method offers two advantages over the other competing methods: the reliability in finding the optimal solution and the time required for finding the optimal solution. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： parallel genetic algorithm parameter adaptation

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A Novel parallel Quantum genetic algorithm

A Novel Parallel Quantum Genetic Algorithm

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The Fourth International Conference on parallel and Distributed Computing, Applications and Technologies

作者： Gexiang Zhang Weidong Jin Laizhao Hu National EW Laboratory School of Electrical Engineering Southwest Jiaotong University China Electronics Technology Group Corporation No.29 Research Institute

In this paper,a novel parallel evolutionary algorithm called coarse-grained parallel quantum genetic algorithm(CGPQGA) is *** main points of CGPQGA are that a new chromosome representation called qubit representation,a novel evolutionary strategy called qubit phase comparison approach and an extended version of coarse-grained model called hierarchical ring model are *** on the concepts and principles of quantum computing and quantum parallelism introduced, CGPQGA is characterized by rapid convergence,good global search capability and the ability of possessing exploration and exploitation *** CGPQGA, the best individual can be easy to migrate to all processors and communication overhead is much less *** experimental results of infinite impulse response digital filter design demonstrate that CGPQGA can speedup the migration of the top individuals of subpopulations and CGPQGA is superior to other several genetic algorithms greatly in quality and efficiency.

关键词： quantum genetic algorithm parallel genetic algorithm coarse-grained mode IIR digital filter

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The parallel genetic algorithm for electromagnetic inverse scattering of a conductor

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2002年第5期79卷 573-586页

作者： Fan, Y Jiang, T Evans, DJ Nottingham Trent Univ Dept Comp Nottingham NG1 4BU England Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100080 Peoples R China

A parallel genetic algorithm is presented to solve the inverse scattering problem which is formulated as an optimal problem where the cost function to be minimized is the energy norm of the residual, i.e. the difference between the estimated and observed field, and the parameters are the unknown control points for using a spline curve to construct the shape of the object conductor. This approach is computationally heavy since the direct problem needs to be solved in every optimization iteration in order to compute an estimated field. Experiments demonstrate our PGA provides an efficient method for such a problem.

关键词： inverse scattering parallel genetic algorithm moment method and cubic spline

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A heuristic approach for detecting RNA H-type pseudoknots

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BIOINFORMATICS 2005年第17期21卷 3501-3508页

作者： Huang, CH Lu, CL Chiu, HT Natl Chiao Tung Univ Dept Biol Sci & Technol Hsinchu 300 Taiwan

Motivation: RNA H-type pseudoknots are ubiquitous pseudoknots that are found in almost all classes of RNA and thought to play very important roles in a variety of biological processes. Detection of these RNA H-type pseudoknots can improve our understanding of RNA structures and their associated functions. However, the currently existing programs for detecting such RNA H-type pseudoknots are still time consuming and sometimes even ineffective. Therefore, efficient and effective tools for detecting the RNA H-type pseudoknots are needed. Results: In this paper, we have adopted a heuristic approach to develop a novel tool, called HPknotter, for efficiently and accurately detecting H-type pseudoknots in an RNA sequence. In addition, we have demonstrated the applicability and effectiveness of HPknotter by testing on some sequences with known H-type pseudoknots. Our approach can be easily extended and applied to other classes of more general pseudoknots.

关键词： parallel genetic algorithm MOSAIC-VIRUS RNA SECONDARY STRUCTURE COMPUTER-SIMULATION INCLUDING PSEUDOKNOTS STRUCTURE PREDICTION INFORMATION THERMODYNAMICS IMPLEMENTATION REPLICATION

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Structural polymorphism of the HIV-1 leader region explored by computational methods

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NUCLEIC ACIDS RESEARCH 2005年第22期33卷 7151-7163页

作者： Kasprzak, W Bindewald, E Shapiro, BA NCI Frederick SAIC Frederick Basic Res Program Frederick MD 21702 USA NCI Frederick Natl Canc Inst Ctr Canc Res Nanbiol Program Frederick MD 21702 USA

Experimental studies revealed that the elements of the human immunodeficiency virus type 1 (HIV-1) 5'-untranslated leader region (5'-UTR) can fold in vitro into two alternative conformations, branched (BMH) and 'linearized' (LDI) and switch between them to achieve different functionality. In this study we computationally explored in detail, with our massively parallel genetic algorithm (MPGAfold), the propensity of 13 HIV-1 5'-UTRs to fold into the BMH and the LDI conformation types. Besides the BMH conformations these results predict the existence of two functionally equivalent types of LDI conformations. One is similar to what has been shown in vitro to exist in HIV-1 LAI, the other is a novel conformation exemplified by HIV-1 MAL long-distance interactions. These novel MPGAfold results are further corroborated by a consensus probability matrix algorithm applied to a set of 155 HIV-1 sequences. We also have determined in detail the impact of various strain mutations, domain sizes and folds of elongating sequences simulating folding during transcription on HIV-1 RNA secondary structure folding dynamics.

关键词： HUMAN-IMMUNODEFICIENCY-VIRUS parallel genetic algorithm RNA SECONDARY STRUCTURE PRIMER ACTIVATION SIGNAL DIMERIZATION INITIATION SITE IN-VITRO EVIDENCE REVERSE TRANSCRIPTION GENOMIC-RNA STRUCTURE PREDICTION PACKAGING SIGNAL Transcription Initiation Site computational methods LDI Reverse Transcription HIV-1 HIV

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parallel genetic algorithms for third generation mobile network planning

Parallel genetic algorithms for third generation mobile netw...

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4th International Conference on parallel Computing in Electrical Engineering (PARELECT 2004)

作者： Maple, C Guo, L Zhang, J Univ Luton Dept Comp & Informat Syst Luton LU1 3JU Beds England

ISBN: (纸本)0769520804

As Third Generation (3G) mobile networks start to be implemented, there is a need for effective network planning. However, deciding upon the optimum placement for the base stations of the networks is a complex task requiring vast computational resource. This paper discusses the conflicting objectives of base station planning and characterises a multi-objective optimisation problem. We present a genetic encoding of the third generation mobile network planning problem and parallel genetic algorithms to solve it.

关键词： 3G CDMA parallel genetic algorithm optimisation coverage capacity

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Multi-niche crowding in the development of parallel genetic simulated annealing 05

Multi-niche crowding in the development of parallel genetic ...

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Proceedings of the 7th annual conference on genetic and evolutionary computation

作者： Zhi-Gang Wang M. Rahman Yoke-San Wong National University of Singapore Singapore

ISBN: (纸本)9781595930101

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from the local optima. Then, the idea of hierarchical parallel GA is borrowed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of parallel GSA. The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. Multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel GA and the breeder genetic algorithm.

关键词： parallel genetic algorithm genetic algorithm simulated annealing

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Solving the Independent-set Problem in a DNA-Based Supercomputer Model

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parallel PROCESSING LETTERS 2005年第4期15卷 469-479页

作者： Chang, Weng-Long Guo, Minyi Wu, Jesse Southern Taiwan Univ Technol Dept Informat Management Tainan 701 Taiwan Univ Aizu Dept Comp Software Aizu Wakamatsu Fukushima 9658580 Japan Natl Kaohsiung Normal Univ Dept Math Kaohsiung 802 Taiwan

In this paper, it is demonstrated how the DNA (DeoxyriboNucleic Acid) operations presented by Adleman and Lipton can be used to develop the parallel genetic algorithm that solves the independent-set problem. The advantage of the genetic algorithm is the huge parallelism inherent in DNA based computing. Furthermore, this work represents obvious evidence for the ability of DNA based parallel computing to solve NP-complete problems.

关键词： DNA based computing parallelism parallel genetic algorithm NP-complete problems

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parallel genetic algorithm for optimizing run-time reconfigurable circuits

Parallel genetic algorithm for optimizing run-time reconfigu...

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10th Mediterranean Electrotechnical Conference on Information Technology and Electrotechnology for the Mediterranean Countries

作者： Fröhlich, H Kosir, A Zajc, B Univ Ljubljana Fac Elect Engn Ljubljana 1000 Slovenia

ISBN: (纸本)078036290X

In this paper a methodology for finding the maximal common subgraph of two directed graphs with parallel genetic algorithm is discussed. The method is directly applicable to the optimization of configurations of FPGA (Field Programmable Gate Array) circuits in Run-Time Reconfigurable systems. The problem of finding the maximal common subgraph is known to be NP-complete. The advantage of our approach is that we find optimal or near-optimal solutions in polynomial time using a genetic algorithm. Since the cost function of the optimization task is multimodal, an implementation of parallel genetic algorithm assures significant improvments of the results.

关键词： reconfigurable circuits parallel genetic algorithm

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A new model of global parallel genetic algorithm

A new model of global parallel genetic algorithm

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22nd International Conference on Information Technology Interfaces (ITI 2000)

作者： Golub, M Jakobovic, D Univ Zagreb Fac Elect Engn & Comp Dept Elect Microelect Comp & Intelligent Syst Zagreb 10000 Croatia

ISBN: (纸本)9539676916

In this paper we describe a multithreaded parallel genetic algorithm (PGA) implementation. Considering the basic models of parallel genetic algorithms, we identify, a variant of global PGA (GPGA) as the most appropriate one for use on a microprocessor system with few processors. The difference between the synchronous and asynchronous model is analized and their characteristics are evaluated. Unlike some authors, we choose not to allow a single individual to be engaged in a tournament competition in more than orle instance (no duplicates). The probability of selection for elimination of an individual is than determined based on the fitness of the chromosome and compared with the same probability of the duplicate-allowing algorithm. Finally, main advantages and disadvantages of our GPGA as well as performance comparison with sequential GA are stated.

关键词： parallel genetic algorithm multithreading tournament selection

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