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IEEE Transactions on Evolutionary Computation

Issue 1 • Date Feb. 2007

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Displaying Results 1 - 13 of 13
  • 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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  • Nonlinear Least Square Regression by Adaptive Domain Method With Multiple Genetic Algorithms

    Publication Year: 2007, Page(s):1 - 16
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (888 KB) | HTML iconHTML

    In conventional least square (LS) regressions for nonlinear problems, it is not easy to obtain analytical derivatives with respect to target parameters that comprise a set of normal equations. Even if the derivatives can be obtained analytically or numerically, one must take care to choose the correct initial values for the iterative procedure of solving an equation, because some undesired, locall... View full abstract»

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  • An Investigation on Preference Order Ranking Scheme for Multiobjective Evolutionary Optimization

    Publication Year: 2007, Page(s):17 - 45
    Cited by:  Papers (84)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2353 KB) | HTML iconHTML

    It may be generalized that all Evolutionary Algorithms (EA) draw their strength from two sources: exploration and exploitation. Surprisingly, within the context of multiobjective (MO) optimization, the impact of fitness assignment on the exploration-exploitation balance has drawn little attention. The vast majority of multiobjective evolutionary algorithms (MOEAs) presented to date resort to Paret... View full abstract»

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  • Combining Neural Networks and Genetic Algorithms to Predict and Reduce Diesel Engine Emissions

    Publication Year: 2007, Page(s):46 - 55
    Cited by:  Papers (46)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (667 KB) | HTML iconHTML

    Diesel engines are fuel efficient which benefits the reduction of CO2 released to the atmosphere compared with gasoline engines, but still result in negative environmental impact related to their emissions. As new degrees of freedom are created, due to advances in technology, the complicated processes of emission formation are difficult to assess. This paper studies the feasibility of u... View full abstract»

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  • An Evolutionary Approach to Multiobjective Clustering

    Publication Year: 2007, Page(s):56 - 76
    Cited by:  Papers (214)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1069 KB) | HTML iconHTML

    The framework of multiobjective optimization is used to tackle the unsupervised learning problem, data clustering, following a formulation first proposed in the statistics literature. The conceptual advantages of the multiobjective formulation are discussed and an evolutionary approach to the problem is developed. The resulting algorithm, multiobjective clustering with automatic k-determination, i... View full abstract»

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  • Christiansen Grammar Evolution: Grammatical Evolution With Semantics

    Publication Year: 2007, Page(s):77 - 90
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3141 KB) | HTML iconHTML

    This paper describes Christiansen grammar evolution (CGE), a new evolutionary automatic programming algorithm that extends standard grammar evolution (GE) by replacing context-free grammars by Christiansen grammars. GE only takes into account syntactic restrictions to generate valid individuals. CGE adds semantics to ensure that both semantically and syntactically valid individuals are generated. ... View full abstract»

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  • The Dandelion Code: A New Coding of Spanning Trees for Genetic Algorithms

    Publication Year: 2007, Page(s):91 - 100
    Cited by:  Papers (20)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (644 KB) | HTML iconHTML

    There are many applications where it is necessary to find an optimal spanning tree. For several of these, recent research has suggested the use of genetic algorithms (GAs). Historically, the Pruumlfer code has been one of the most popular representations for spanning trees, due largely to the bijective mapping between genotype and phenotype. However, it is has attracted much criticism for its low ... View full abstract»

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  • An Immune Algorithm for Protein Structure Prediction on Lattice Models

    Publication Year: 2007, Page(s):101 - 117
    Cited by:  Papers (81)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1004 KB) | HTML iconHTML

    We present an immune algorithm (IA) inspired by the clonal selection principle, which has been designed for the protein structure prediction problem (PSP). The proposed IA employs two special mutation operators, hypermutation and hypermacromutation to allow effective searching, and an aging mechanism which is a new immune inspired operator that is devised to enforce diversity in the population dur... View full abstract»

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  • Synapsing Variable-Length Crossover: Meaningful Crossover for Variable-Length Genomes

    Publication Year: 2007, Page(s):118 - 131
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1802 KB) | HTML iconHTML

    The synapsing variable-length crossover (SVLC) algorithm provides a biologically inspired method for performing meaningful crossover between variable-length genomes. In addition to providing a rationale for variable-length crossover, it also provides a genotypic similarity metric for variable-length genomes, enabling standard niche formation techniques to be used with variable-length genomes. Unli... View full abstract»

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    Publication Year: 2007, Page(s): 132
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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