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IEEE Transactions on Evolutionary Computation

Issue 4 • Date Aug. 2004

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Displaying Results 1 - 13 of 13
  • Table of contents

    Publication Year: 2004, Page(s): c1
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  • IEEE Transactions on Evolutionary Computation publication information

    Publication Year: 2004, Page(s): c2
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  • Hybrid coevolutionary programming for Nash equilibrium search in games with local optima

    Publication Year: 2004, Page(s):305 - 315
    Cited by:  Papers (41)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (544 KB) | HTML iconHTML

    The conventional local optimization path and coevolutionary processes are studied when "local Nash equilibrium (NE) traps" exist. Conventional NE search algorithms in games with local optima can misidentify NE by following a local optimization path. We prove that any iterative NE search algorithms based on local optimization cannot differentiate real NE and "local NE traps". Coevolutionary program... View full abstract»

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  • Learning with case-injected genetic algorithms

    Publication Year: 2004, Page(s):316 - 328
    Cited by:  Papers (35)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1048 KB) | HTML iconHTML

    This paper presents a new approach to acquiring and using problem specific knowledge during a genetic algorithm (GA) search. A GA augmented with a case-based memory of past problem solving attempts learns to obtain better performance over time on sets of similar problems. Rather than starting anew on each problem, we periodically inject a GA's population with appropriate intermediate solutions to ... View full abstract»

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  • A GA-based design space exploration framework for parameterized system-on-a-chip platforms

    Publication Year: 2004, Page(s):329 - 346
    Cited by:  Papers (29)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1016 KB) | HTML iconHTML

    The constant increase in levels of integration and reduction in the time-to-market has led to the definition of new methodologies, which lay emphasis on reuse. One emerging approach in this context is platform-based design. The basic idea is to avoid designing a chip from scratch. Some portions of the chip's architecture are predefined for a specific type of application. This implies that the basi... View full abstract»

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  • On-line genetic design of anti-windup unstructured controllers for electric drives with variable load

    Publication Year: 2004, Page(s):347 - 364
    Cited by:  Papers (41)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (904 KB) | HTML iconHTML

    In this paper, we describe an evolutionary design procedure for discrete-time anti-windup controller for electrical drives. Using a genetic algorithm devised to test and compare controllers of different orders, we search for the discrete anti-windup controller achieving the optimal compromise of weighted cost and performance indices. The search is performed on-line, on the physical hardware, by co... View full abstract»

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  • Hybrid Taguchi-genetic algorithm for global numerical optimization

    Publication Year: 2004, Page(s):365 - 377
    Cited by:  Papers (192)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (520 KB) | HTML iconHTML

    In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is proposed to solve global numerical optimization problems with continuous variables. The HTGA combines the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a T... View full abstract»

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  • An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach

    Publication Year: 2004, Page(s):378 - 404
    Cited by:  Papers (33)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1384 KB) | HTML iconHTML

    Given the explosive growth of data collected from current business environment, data mining can potentially discover new knowledge to improve managerial decision making. This paper proposes a novel data mining approach that employs an evolutionary algorithm to discover knowledge represented in Bayesian networks. The approach is applied successfully to handle the business problem of finding respons... View full abstract»

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  • Statistical exploratory analysis of genetic algorithms

    Publication Year: 2004, Page(s):405 - 421
    Cited by:  Papers (22)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1184 KB) | HTML iconHTML

    Genetic algorithms have been extensively used and studied in computer science, yet there is no generally accepted methodology for exploring which parameters significantly affect performance, whether there is any interaction between parameters, and how performance varies with respect to changes in parameters. This paper presents a rigorous yet practical statistical methodology for the exploratory s... View full abstract»

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  • Ant Colony Optimization

    Publication Year: 2004, Page(s):422 - 423
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  • IEEE symposium on computational intelligence and games

    Publication Year: 2004, Page(s): 424
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  • IEEE Neural Networks Society Information

    Publication Year: 2004, Page(s): c3
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  • IEEE Transactions on Evolutionary Computation Information for authors

    Publication Year: 2004, 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