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IEEE Transactions on Evolutionary Computation

Issue 4 • Date Nov. 2000

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Displaying Results 1 - 10 of 10
  • Acknowledgment to reviewers

    Publication Year: 2000, Page(s):394 - 395
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    Freely Available from IEEE
  • Author index

    Publication Year: 2000, Page(s):396 - 398
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    Freely Available from IEEE
  • Subject index

    Publication Year: 2000, Page(s):398 - 402
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    Freely Available from IEEE
  • Designing classifier fusion systems by genetic algorithms

    Publication Year: 2000, Page(s):327 - 336
    Cited by:  Papers (91)  |  Patents (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (376 KB)

    We suggest two simple ways to use a genetic algorithm (GA) to design a multiple-classifier system. The first GA version selects disjoint feature subsets to be used by the individual classifiers, whereas the second version selects (possibly) overlapping feature subsets, and also the types of the individual classifiers. The two GAs have been tested with four real data sets: heart, Satimage, letters,... View full abstract»

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  • Evolutionary ensembles with negative correlation learning

    Publication Year: 2000, Page(s):380 - 387
    Cited by:  Papers (149)  |  Patents (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (128 KB)

    Based on negative correlation learning and evolutionary learning, this paper presents evolutionary ensembles with negative correlation learning (EENCL) to address the issues of automatic determination of the number of individual neural networks (NNs) in an ensemble and the exploitation of the interaction between individual NN design and combination. The idea of EENCL is to encourage different indi... View full abstract»

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  • Fitness landscape analysis and memetic algorithms for the quadratic assignment problem

    Publication Year: 2000, Page(s):337 - 352
    Cited by:  Papers (197)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (372 KB)

    In this paper, a fitness landscape analysis for several instances of the quadratic assignment problem (QAP) is performed, and the results are used to classify problem instances according to their hardness for local search heuristics and meta-heuristics based on local search. The local properties of the fitness landscape are studied by performing an autocorrelation analysis, while the global struct... View full abstract»

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  • Resource sharing and coevolution in evolving cellular automata

    Publication Year: 2000, Page(s):388 - 393
    Cited by:  Papers (20)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (168 KB)

    Coevolution, between a population of candidate solutions and a population of test cases, has received increasing attention as a promising biologically inspired method for improving the performance of evolutionary computation techniques. However, the results of studies of coevolution have been mixed. One of the seemingly more impressive results to date was the improvement via coevolution demonstrat... View full abstract»

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  • A hybrid evolutionary approach for solving constrained optimization problems over finite domains

    Publication Year: 2000, Page(s):353 - 372
    Cited by:  Papers (8)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (828 KB)

    A novel approach for the integration of evolution programs and constraint-solving techniques over finite domains is presented. This integration provides a problem-independent optimization strategy for large-scale constrained optimization problems over finite domains. In this approach, genetic operators are based on an arc-consistency algorithm, and chromosomes are arc-consistent portions of the se... View full abstract»

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  • Application of evolutionary programming to adaptive regularization in image restoration

    Publication Year: 2000, Page(s):309 - 326
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (548 KB)

    Image restoration is a difficult problem due to the ill-conditioned nature of the associated inverse filtering operation, which requires regularization techniques. The choice of the corresponding regularization parameter is thus an important issue since an incorrect choice would either lead to noisy appearances in the smooth regions or excessive blurring of the textured regions. In addition, this ... View full abstract»

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  • The computational complexity of N-K fitness functions

    Publication Year: 2000, Page(s):373 - 379
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (140 KB)

    N-K fitness landscapes have been used widely as examples and test functions in the field of evolutionary computation. We investigate the computational complexity of the problem of optimizing the N-K fitness functions and related fitness functions. We give an algorithm to optimize adjacent-model N-K fitness functions, which is polynomial in N. We show that the decision problem corresponding to opti... View full abstract»

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Aims & Scope

IEEE Transactions on Evolutionary Computation publishes archival quality original papers in evolutionary computation and related areas including nature-inspired algorithms, population-based methods, and optimization where selection and variation are integral, and hybrid systems where these paradigms are combined. Purely theoretical papers are considered as are application papers that provide general insights into these areas of computation.
 

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Meet Our Editors

Editor-in-Chief

Dr. Kay Chen Tan (IEEE Fellow)

Department of Electrical and Computer Engineering

National University of Singapore

Singapore 117583

Email: eletankc@nus.edu.sg

Website: http://vlab.ee.nus.edu.sg/~kctan