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IEEE Transactions on Evolutionary Computation

Issue 6 • Dec. 2006

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Displaying Results 1 - 16 of 16
  • Table of contents

    Publication Year: 2006, Page(s): C1
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  • IEEE Transactions on Evolutionary Computation publication information

    Publication Year: 2006, Page(s): C2
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  • Biasing Coevolutionary Search for Optimal Multiagent Behaviors

    Publication Year: 2006, Page(s):629 - 645
    Cited by:  Papers (27)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1914 KB) | HTML iconHTML

    Cooperative coevolutionary algorithms (CEAs) offer great potential for concurrent multiagent learning domains and are of special utility to domains involving teams of multiple agents. Unfortunately, they also exhibit pathologies resulting from their game-theoretic nature, and these pathologies interfere with finding solutions that correspond to optimal collaborations of interacting agents. We addr... View full abstract»

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  • Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems

    Publication Year: 2006, Page(s):646 - 657
    Cited by:  Papers (1043)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1042 KB) | HTML iconHTML

    We describe an efficient technique for adapting control parameter settings associated with differential evolution (DE). The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters, which are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE... View full abstract»

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  • A Multiobjective Optimization-Based Evolutionary Algorithm for Constrained Optimization

    Publication Year: 2006, Page(s):658 - 675
    Cited by:  Papers (158)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1640 KB) | HTML iconHTML

    A considerable number of constrained optimization evolutionary algorithms (COEAs) have been proposed due to increasing interest in solving constrained optimization problems (COPs) by evolutionary algorithms (EAs). In this paper, we first review existing COEAs. Then, a novel EA for constrained optimization is presented. In the process of population evolution, our algorithm is based on multiobjectiv... View full abstract»

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  • Evolutionary Design of Neural Network Architectures Using a Descriptive Encoding Language

    Publication Year: 2006, Page(s):676 - 688
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (732 KB) | HTML iconHTML

    Evolutionary algorithms are a promising approach to the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to represent repetitive and recurrent modules in networks. We present a problem-independent approach based on a human-readable and writable descriptive encoding using a high-level language. This encoding is based on developmental m... View full abstract»

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  • Clearance of Nonlinear Flight Control Laws Using Hybrid Evolutionary Optimization

    Publication Year: 2006, Page(s):689 - 699
    Cited by:  Papers (33)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (606 KB) | HTML iconHTML

    The application of two evolutionary optimization methods, namely, differential evolution and genetic algorithms, to the clearance of nonlinear flight control laws for highly augmented aircraft is described. The algorithms are applied to the problem of evaluating a nonlinear handling quality clearance criterion for a simulation model of a high-performance aircraft with a delta canard configuration ... View full abstract»

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  • Improved Heuristics for the Minimum Label Spanning Tree Problem

    Publication Year: 2006, Page(s):700 - 703
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (312 KB) | HTML iconHTML

    Given a connected, undirected graph G whose edges are labeled, the minimum label (or labeling) spanning tree (MLST) problem seeks a spanning tree on G with the minimum number of distinct labels. Maximum vertex covering algorithm (MVCA) is a well-known heuristic for the MLST problem. It is very fast and performs reasonably well. Recently, we developed a genetic algorithm (GA) for the MLST problem. ... View full abstract»

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  • Acknowledgment to Reviewers

    Publication Year: 2006, Page(s):704 - 706
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  • Special issue on evolutionary computation for finance and economics

    Publication Year: 2006, Page(s): 707
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  • IEEE Congress on Evolutionary Computation

    Publication Year: 2006, Page(s): 708
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  • Special issue on evolutionary algorithms based on probabilistic models

    Publication Year: 2006, Page(s): 709
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  • Put your technology leadership in writing

    Publication Year: 2006, Page(s): 710
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  • 2006 Index

    Publication Year: 2006, Page(s):711 - 716
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  • IEEE Computational Intelligence Society Information

    Publication Year: 2006, Page(s): C3
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  • IEEE Transactions on Evolutionary Computation Information for authors

    Publication Year: 2006, Page(s): C4
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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: kaytan@cityu.edu.hk

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