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IEEE Transactions on Evolutionary Computation

Issue 5 • Date Oct. 2002

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Displaying Results 1 - 9 of 9
  • In memoriam Alex S. Fraser [1923-2002]

    Publication Year: 2002, Page(s):429 - 430
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    Freely Available from IEEE
  • Multi-objective optimization using evolutionary algorithms [Book Review]

    Publication Year: 2002, Page(s): 526
    Cited by:  Papers (2)
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    Freely Available from IEEE
  • Parallelism and evolutionary algorithms

    Publication Year: 2002, Page(s):443 - 462
    Cited by:  Papers (207)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (366 KB) | HTML iconHTML

    This paper contains a modern vision of the parallelization techniques used for evolutionary algorithms (EAs). The work is motivated by two fundamental facts: 1) the different families of EAs have naturally converged in the last decade while parallel EAs (PEAs) are still lack of unified studies; and 2) there is a large number of improvements in these algorithms and in their parallelization that rai... View full abstract»

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  • An evolutionary algorithm for resource-constrained project scheduling

    Publication Year: 2002, Page(s):512 - 518
    Cited by:  Papers (26)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (256 KB) | HTML iconHTML

    The single-mode, single-project, resource-constrained project-scheduling problem is solved by an evolutionary algorithm. The design of this algorithm is presented. Results of a computational study on two sets of benchmark problems, the first consisting of 330 problem instances and the second 2040, are presented. These results show that the proposed algorithm is effective in terms of the number of ... View full abstract»

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  • A framework for evolutionary optimization with approximate fitness functions

    Publication Year: 2002, Page(s):481 - 494
    Cited by:  Papers (131)  |  Patents (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (439 KB) | HTML iconHTML

    It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are unclear due to the approximation error of the model. In this paper, extensive empirical studies are carried out to investigate the convergence properties of an evolution strategy using an approximate fitness function on... View full abstract»

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  • NOW G-Net: learning classification programs on networks of workstations

    Publication Year: 2002, Page(s):463 - 480
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (413 KB) | HTML iconHTML

    The automatic construction of classifiers (programs able to correctly classify data collected from the real world) is one of the major problems in pattern recognition and in a wide area related to artificial intelligence, including data mining. We present G-Net, a distributed evolutionary algorithm able to infer classifiers from precollected data. The main features of the system include robustness... View full abstract»

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  • Genetic programming and evolutionary generalization

    Publication Year: 2002, Page(s):431 - 442
    Cited by:  Papers (21)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (248 KB) | HTML iconHTML

    In genetic programming (GP), learning problems can be classified broadly into two types: those using data sets, as in supervised learning, and those using an environment as a source of feedback. An increasing amount of research has concentrated on the robustness or generalization ability of the programs evolved using GP. While some of the researchers report on the brittleness of the solutions evol... View full abstract»

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  • Genetic-fuzzy approach to the Boolean satisfiability problem

    Publication Year: 2002, Page(s):519 - 525
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (428 KB) | HTML iconHTML

    This study is concerned with the Boolean satisfiability (SAT) problem and its solution in setting a hybrid computational intelligence environment of genetic and fuzzy computing. In this framework, fuzzy sets realize an embedding principle meaning that original two-valued (Boolean) functions under investigation are extended to their continuous counterparts resulting in the form of fuzzy (multivalue... View full abstract»

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  • From an individual to a population: an analysis of the first hitting time of population-based evolutionary algorithms

    Publication Year: 2002, Page(s):495 - 511
    Cited by:  Papers (57)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (574 KB) | HTML iconHTML

    Almost all analyses of time complexity of evolutionary algorithms (EAs) have been conducted for (1 + 1) EAs only. Theoretical results on the average computation time of population-based EAs are few. However, the vast majority of applications of EAs use a population size that is greater than one. The use of population has been regarded as one of the key features of EAs. It is important to understan... 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.
 

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