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IEEE Transactions on Evolutionary Computation

Issue 3 • Date June 2009

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Displaying Results 1 - 19 of 19
  • Table of contents

    Publication Year: 2009, Page(s): C1
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  • IEEE Transactions on Evolutionary Computation publication information

    Publication Year: 2009, Page(s): C2
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  • Towards the Validation of Plagiarism Detection Tools by Means of Grammar Evolution

    Publication Year: 2009, Page(s):477 - 485
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1521 KB) | HTML iconHTML

    Student plagiarism is a major problem in universities worldwide. In this paper, we focus on plagiarism in answers to computer programming assignments, where students mix and/or modify one or more original solutions to obtain counterfeits. Although several software tools have been developed to help the tedious and time consuming task of detecting plagiarism, little has been done to assess their qua... View full abstract»

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  • On the Bias and Performance of the Edge-Set Encoding

    Publication Year: 2009, Page(s):486 - 499
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1261 KB) | HTML iconHTML

    The edge-set encoding of trees directly represents trees as sets of their edges. Nonheuristic operators for edge-sets manipulate trees' edges without regard for their weights, while heuristic operators consider edges' weights when including or excluding them. In the latter case, the operators generally favor edges with lower weights, and they tend to generate trees that resemble minimum spanning t... View full abstract»

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  • Dynamic Evolutionary Algorithm With Variable Relocation

    Publication Year: 2009, Page(s):500 - 513
    Cited by:  Papers (35)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (655 KB) | HTML iconHTML

    Many real-world optimization problems have to be solved under the presence of uncertainties. A significant number of these uncertainty problems falls into the dynamic optimization category in which the fitness function varies through time. For this class of problems, an evolutionary algorithm is expected to perform satisfactorily in spite of different degrees and frequencies of change in the fitne... View full abstract»

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  • Constraint Handling in Multiobjective Evolutionary Optimization

    Publication Year: 2009, Page(s):514 - 525
    Cited by:  Papers (63)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1141 KB) | HTML iconHTML

    This paper proposes a constraint handling technique for multiobjective evolutionary algorithms based on an adaptive penalty function and a distance measure. These two functions vary dependent upon the objective function value and the sum of constraint violations of an individual. Through this design, the objective space is modified to account for the performance and constraint violation of each in... View full abstract»

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  • Differential Evolution Using a Neighborhood-Based Mutation Operator

    Publication Year: 2009, Page(s):526 - 553
    Cited by:  Papers (378)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1264 KB) | HTML iconHTML

    Differential evolution (DE) is well known as a simple and efficient scheme for global optimization over continuous spaces. It has reportedly outperformed a few evolutionary algorithms (EAs) and other search heuristics like the particle swarm optimization (PSO) when tested over both benchmark and real-world problems. DE, however, is not completely free from the problems of slow and/or premature con... View full abstract»

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  • Optimal Strategies of the Iterated Prisoner's Dilemma Problem for Multiple Conflicting Objectives

    Publication Year: 2009, Page(s):554 - 565
    Cited by:  Papers (16)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (442 KB) | HTML iconHTML

    In this paper, we present a new paradigm of searching optimal strategies in the game of iterated prisoner's dilemma (IPD) using multiple-objective evolutionary algorithms. This method is more useful than the existing approaches, because it not only produces strategies that perform better in the iterated game but also finds a family of nondominated strategies, which can be analyzed to decipher prop... View full abstract»

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  • Search, Neutral Evolution, and Mapping in Evolutionary Computing: A Case Study of Grammatical Evolution

    Publication Year: 2009, Page(s):566 - 590
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1322 KB) | HTML iconHTML

    We present a new perspective of search in evolutionary computing (EC) by using a novel model for the analysis and visualization of genotype to phenotype maps. The model groups genes into quotient sets and shows their adjacencies. A unique quality of the quotient model is that it details geometric qualities of maps that are not otherwise easy to observe. The model shows how random mutations on gene... View full abstract»

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  • On the Effects of Adding Objectives to Plateau Functions

    Publication Year: 2009, Page(s):591 - 603
    Cited by:  Papers (23)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (565 KB) | HTML iconHTML

    In this paper, we examine how adding objectives to a given optimization problem affects the computational effort required to generate the set of Pareto-optimal solutions. Experimental studies show that additional objectives may change the running time behavior of an algorithm drastically. Often it is assumed that more objectives make a problem harder as the number of different tradeoffs may increa... View full abstract»

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  • A Probabilistic Memetic Framework

    Publication Year: 2009, Page(s):604 - 623
    Cited by:  Papers (127)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (920 KB) | HTML iconHTML

    Memetic algorithms (MAs) represent one of the recent growing areas in evolutionary algorithm (EA) research. The term MAs is now widely used as a synergy of evolutionary or any population-based approach with separate individual learning or local improvement procedures for problem search. Quite often, MAs are also referred to in the literature as Baldwinian EAs, Lamarckian EAs, cultural algorithms, ... View full abstract»

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  • Arc-Guided Evolutionary Algorithm for the Vehicle Routing Problem With Time Windows

    Publication Year: 2009, Page(s):624 - 647
    Cited by:  Papers (33)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (642 KB) | HTML iconHTML

    This paper presents an arc-guided evolutionary algorithm for solving the vehicle routing problem with time windows, which is a well-known combinatorial optimization problem that addresses the service of a set of customers using a homogeneous fleet of capacitated vehicles within fixed time intervals. The objective is to minimize the fleet size following routes of minimum distance. The proposed meth... View full abstract»

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  • Genetic Team Composition and Level of Selection in the Evolution of Cooperation

    Publication Year: 2009, Page(s):648 - 660
    Cited by:  Papers (34)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (765 KB) | HTML iconHTML

    In cooperative multiagent systems, agents interact to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules (ldquogenetically homogeneous teamsrdquo)... View full abstract»

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  • Preserving and Exploiting Genetic Diversity in Evolutionary Programming Algorithms

    Publication Year: 2009, Page(s):661 - 673
    Cited by:  Papers (27)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (703 KB) | HTML iconHTML

    Evolution programming (EP) is an important category of evolutionary algorithms. It relies primarily on mutation operators to search for solutions of function optimization problems (FOPs). Recently a series of new mutation operators have been proposed in order to improve the performance of EP. One prominent example is the fast EP (FEP) algorithm which employs a mutation operator based on the Cauchy... View full abstract»

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  • Special issue on preference-based multiobjective evolutionary algorithms

    Publication Year: 2009, Page(s): 674
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    Publication Year: 2009, Page(s): 675
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    Publication Year: 2009, Page(s): 676
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  • IEEE Computational Intelligence Society Information

    Publication Year: 2009, Page(s): C3
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  • IEEE Transactions on Evolutionary Computation Information for authors

    Publication Year: 2009, 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