IEEE Transactions on Evolutionary Computation

Issue 6 • Dec. 2013

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Displaying Results 1 - 14 of 14
  • Table of contents

    Publication Year: 2013, Page(s): C1
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  • IEEE Transactions on Evolutionary Computation publication information

    Publication Year: 2013, Page(s): C2
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  • Striking a Mean- and Parent-Centric Balance in Real-Valued Crossover Operators

    Publication Year: 2013, Page(s):737 - 754
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1916 KB) | HTML iconHTML

    This paper investigates the mean- and parent-centric balance in real-valued crossover operators, which is strongly related to the powerful and efficient optimization performance. To treat the property as a continuous value, a novel crossover operator, called asymmetrical normal distribution crossover (ANDX), has been introduced. Because the crossover operator has a tunable parameter for the mean- ... View full abstract»

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  • Multiobjective Particle Swarm Optimization With Preference-Based Sort and Its Application to Path Following Footstep Optimization for Humanoid Robots

    Publication Year: 2013, Page(s):755 - 766
    Cited by:  Papers (28)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1067 KB) | HTML iconHTML

    This paper proposes multiobjective particle swarm optimization with preference-based sort (MOPSO-PS), in which the user's preference is incorporated into the particle swarm optimization (PSO) update process to determine the relative merits of nondominated solutions while handling the mutual dependences and priorities of objectives. In MOPSO-PS, the user's preference is represented as the degree of... View full abstract»

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  • An Energy-Based Sampling Technique for Multi-Objective Restricted Boltzmann Machine

    Publication Year: 2013, Page(s):767 - 785
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1204 KB) | HTML iconHTML

    Estimation of distribution algorithms are gaining increased research interest due to their advantage in exploiting linkage information. This paper examines the sampling techniques of a restricted Boltzmann machine-based multi-objective (MO) estimation of distribution algorithm (REDA). The behaviors of the sampling techniques in terms of energy levels are rigorously investigated, and a sampling mec... View full abstract»

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  • An Efficient Evolutionary Algorithm for Chance-Constrained Bi-Objective Stochastic Optimization

    Publication Year: 2013, Page(s):786 - 796
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (229 KB) | HTML iconHTML

    In engineering design and manufacturing optimization, the trade-off between a quality performance metric and the probability of satisfying all performance specifications (yield) of a product naturally leads to a chance-constrained bi-objective stochastic optimization problem (CBSOP). A new method, called MOOLP (multi-objective uncertain optimization with ordinal optimization (OO)), Latin supercube... View full abstract»

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  • Scaling Up Estimation of Distribution Algorithms for Continuous Optimization

    Publication Year: 2013, Page(s):797 - 822
    Cited by:  Papers (23)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1744 KB) | HTML iconHTML

    Since estimation of distribution algorithms (EDAs) were proposed, many attempts have been made to improve EDAs' performance in the context of global optimization. So far, the studies or applications of multivariate probabilistic model-based EDAs in continuous domain are still mostly restricted to low-dimensional problems. Traditional EDAs have difficulties in solving higher dimensional problems be... View full abstract»

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  • Optimal Cycle Program of Traffic Lights With Particle Swarm Optimization

    Publication Year: 2013, Page(s):823 - 839
    Cited by:  Papers (28)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1219 KB) | HTML iconHTML

    Optimal staging of traffic lights, and in particular optimal light cycle programs, is a crucial task in present day cities with potential benefits in terms of energy consumption, traffic flow management, pedestrian safety, and environmental issues. Nevertheless, very few publications in the current literature tackle this problem by means of automatic intelligent systems, and, when they do, they fo... View full abstract»

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  • Grammatical Evolution Hyper-Heuristic for Combinatorial Optimization Problems

    Publication Year: 2013, Page(s):840 - 861
    Cited by:  Papers (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (40848 KB) | HTML iconHTML

    Designing generic problem solvers that perform well across a diverse set of problems is a challenging task. In this work, we propose a hyper-heuristic framework to automatically generate an effective and generic solution method by utilizing grammatical evolution. In the proposed framework, grammatical evolution is used as an online solver builder, which takes several heuristic components (e.g., di... View full abstract»

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  • Fitness Modeling With Markov Networks

    Publication Year: 2013, Page(s):862 - 879
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1243 KB) | HTML iconHTML

    Fitness modeling has received growing interest from the evolutionary computation community in recent years. With a fitness model, one can improve evolutionary algorithm efficiency by directly sampling new solutions, developing hybrid guided evolutionary operators or using the model as a surrogate for an expensive fitness function. This paper addresses several issues on fitness modeling of discrete... View full abstract»

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  • Acknowledgment to reviewers

    Publication Year: 2013, Page(s):880 - 883
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  • IEEE Xplore Digital Library

    Publication Year: 2013, Page(s): 884
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  • IEEE Computational Intelligence Society Information

    Publication Year: 2013, Page(s): C3
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  • IEEE Transactions on Evolutionary Computation information for authors

    Publication Year: 2013, 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
Professor Kay Chen Tan (IEEE Fellow)
Department of Computer Science
City University of Hong Kong
Kowloon Tong, Kowloon, Hong Kong
Email: kaytan@cityu.edu.hk