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IEEE Transactions on Evolutionary Computation

Issue 3 • Date June 2007

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Displaying Results 1 - 19 of 19
  • Table of contents

    Publication Year: 2007, Page(s): C1
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  • IEEE Transactions on Evolutionary Computation publication information

    Publication Year: 2007, Page(s): C2
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  • In Memoriam: Dr. Lawrence J. Fogel

    Publication Year: 2007, Page(s): 289
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (251 KB)

    Xin Yao recounts the life and career of Dr. Lawrence J. Fogel, a pioneer in evolutionary computation. View full abstract»

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  • In Memoriam: Dr. Lawrence J. Fogel

    Publication Year: 2007, Page(s):290 - 293
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  • Imperfect Evolutionary Systems

    Publication Year: 2007, Page(s):294 - 307
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (703 KB) | HTML iconHTML

    In this paper, we propose a change from a perfect paradigm to an imperfect paradigm in evolving intelligent systems. An imperfect evolutionary system (IES) is introduced as a new approach in an attempt to solve the problem of an intelligent system adapting to new challenges from its imperfect environment, with an emphasis on the incompleteness and continuity of intelligence. We define an IES as a ... View full abstract»

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  • Learning Finite-State Transducers: Evolution Versus Heuristic State Merging

    Publication Year: 2007, Page(s):308 - 325
    Cited by:  Papers (7)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (976 KB) | HTML iconHTML

    Finite-state transducers (FSTs) are finite-state machines (FSMs) that map strings in a source domain into strings in a target domain. While there are many reports in the literature of evolving FSMs, there has been much less work on evolving FSTs. In particular, the fitness functions required for evolving FSTs are generally different from those used for FSMs. In this paper, three string distance-ba... View full abstract»

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  • Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms

    Publication Year: 2007, Page(s):326 - 335
    Cited by:  Papers (95)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (796 KB) | HTML iconHTML

    Research into adjusting the probabilities of crossover and mutation pm in genetic algorithms (GAs) is one of the most significant and promising areas in evolutionary computation. px and pm greatly determine whether the algorithm will find a near-optimum solution or whether it will find a solution efficiently. Instead of using fixed values of px and p... View full abstract»

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  • An Evolutionary Algorithm-Based Approach to Automated Design of Analog and RF Circuits Using Adaptive Normalized Cost Functions

    Publication Year: 2007, Page(s):336 - 353
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1310 KB) | HTML iconHTML

    Typical analog and radio frequency (RF) circuit sizing optimization problems are computationally hard and require the handling of several conflicting cost criteria. Many researchers have used sequential stochastic refinement methods to solve them, where the different cost criteria can either be combined into a single-objective function to find a unique solution, or they can be handled by multiobje... View full abstract»

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  • An Investigation on Noisy Environments in Evolutionary Multiobjective Optimization

    Publication Year: 2007, Page(s):354 - 381
    Cited by:  Papers (54)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2804 KB) | HTML iconHTML

    In addition to satisfying several competing objectives, many real-world applications are also characterized by a certain degree of noise, manifesting itself in the form of signal distortion or uncertain information. In this paper, extensive studies are carried out to examine the impact of noisy environments in evolutionary multiobjective optimization. Three noise-handling features are then propose... View full abstract»

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  • Emerging Cooperation With Minimal Effort: Rewarding Over Mimicking

    Publication Year: 2007, Page(s):382 - 396
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (853 KB) | HTML iconHTML

    This paper compares supervised and unsupervised learning mechanisms for the emergence of cooperative multiagent spatial coordination using a top-down approach. By observing the global performance of a group of homogeneous agents-supported by a nonglobal knowledge of their environment-we attempt to extract information about the minimum size of the agent neurocontroller and the type of learning mech... View full abstract»

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  • Finding Feasible Timetables Using Group-Based Operators

    Publication Year: 2007, Page(s):397 - 413
    Cited by:  Papers (27)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (725 KB) | HTML iconHTML

    This paper describes the applicability of the so-called "grouping genetic algorithm" to a well-known version of the university course timetabling problem. We note that there are, in fact, various scaling up issues surrounding this sort of algorithm and, in particular, see that it behaves in quite different ways with different sized problem instances. As a by-product of these investigations, we int... View full abstract»

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  • Interactive Evolutionary Computation-Based Hearing Aid Fitting

    Publication Year: 2007, Page(s):414 - 427
    Cited by:  Papers (36)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1526 KB) | HTML iconHTML

    An interactive evolutionary computation (EC) fitting method is proposed that applies interactive EC to hearing aid fitting and the method is evaluated using a hearing aid simulator with human subjects. The advantages of the method are that it can optimize a hearing aid based on how a user hears and that it realizes whatever+whenever+wherever (W3) fitting. Conventional fitting methods ar... View full abstract»

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  • IEEE Congress on Evolutionary Computation

    Publication Year: 2007, Page(s): 428
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  • 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

    Publication Year: 2007, Page(s): 429
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  • Pre-submission professional editing services now available

    Publication Year: 2007, Page(s): 430
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  • IEEE Foundation [advertisement]

    Publication Year: 2007, Page(s): 431
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  • Order form for reprints

    Publication Year: 2007, Page(s): 432
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  • IEEE Computational Intelligence Society Information

    Publication Year: 2007, Page(s): C3
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  • IEEE Transactions on Evolutionary Computation Information for authors

    Publication Year: 2007, 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.
 

Full Aims & Scope

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