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Evolutionary Computation, IEEE Transactions on

Issue 5 • Date Oct. 2005

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  • Table of contents

    Publication Year: 2005 , Page(s): c1
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  • IEEE Transactions on Evolutionary Computation publication information

    Publication Year: 2005 , Page(s): c2
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  • Constrained optimization by applying the α constrained method to the nonlinear simplex method with mutations

    Publication Year: 2005 , Page(s): 437 - 451
    Cited by:  Papers (46)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (688 KB) |  | HTML iconHTML  

    Constrained optimization problems are very important and frequently appear in the real world. The α constrained method is a new transformation method for constrained optimization. In this method, a satisfaction level for the constraints is introduced, which indicates how well a search point satisfies the constraints. The α level comparison, which compares search points based on their l... View full abstract»

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  • Gradient descent methods in learning classifier systems: improving XCS performance in multistep problems

    Publication Year: 2005 , Page(s): 452 - 473
    Cited by:  Papers (21)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1928 KB) |  | HTML iconHTML  

    The accuracy-based XCS classifier system has been shown to solve typical data mining problems in a machine-learning competitive way. However, successful applications in multistep problems, modeled by a Markov decision process, were restricted to very small problems. Until now, the temporal difference learning technique in XCS was based on deterministic updates. However, since a prediction is actua... View full abstract»

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  • A tutorial for competent memetic algorithms: model, taxonomy, and design issues

    Publication Year: 2005 , Page(s): 474 - 488
    Cited by:  Papers (216)  |  Patents (1)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (464 KB) |  | HTML iconHTML  

    The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (Moscato, 1989). These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learning within the lifetimes of its members. Additionally, MAs are inspired by Richard Dawkin's concept of a meme, which represents a unit of cultural evol... View full abstract»

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  • Selection intensity in cellular evolutionary algorithms for regular lattices

    Publication Year: 2005 , Page(s): 489 - 505
    Cited by:  Papers (20)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1000 KB) |  | HTML iconHTML  

    In this paper, we present quantitative models for the selection pressure of cellular evolutionary algorithms on regular one- and two-dimensional (2-D) lattices. We derive models based on probabilistic difference equations for synchronous and several asynchronous cell update policies. The models are validated using two customary selection methods: binary tournament and linear ranking. Theoretical r... View full abstract»

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  • Application of the utility function method for behavioral organization in a locomotion task

    Publication Year: 2005 , Page(s): 506 - 521
    Cited by:  Papers (3)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (600 KB) |  | HTML iconHTML  

    The generation of a complete robotic brain for locomotion based on the utility function (UF) method for behavioral organization is demonstrated. A simulated, single-legged hopping robot is considered, and a two-stage process is used for generating the robotic brain. First, individual behaviors are constructed through artificial evolution of recurrent neural networks (RNNs). Thereafter, a behaviora... View full abstract»

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  • A multiagent model of the UK market in electricity generation

    Publication Year: 2005 , Page(s): 522 - 536
    Cited by:  Papers (24)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (648 KB) |  | HTML iconHTML  

    The deregulation of electricity markets has continued apace around the globe. The best structure for deregulated markets is a subject of much debate, and the consequences of poor structural choices can be dramatic. Understanding the effect of structure on behavior is essential, but the traditional economics approaches of field studies and experimental studies are particularly hard to conduct in re... View full abstract»

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  • IEEE Computational Intelligence Society Information

    Publication Year: 2005 , Page(s): c3
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  • IEEE Transactions on Evolutionary Computation Information for authors

    Publication Year: 2005 , 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: eletankc@nus.edu.sg

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