Scheduled System Maintenance
On Tuesday, September 26, IEEE Xplore will undergo scheduled maintenance from 1:00-4:00 PM ET.
During this time, there may be intermittent impact on performance. We apologize for any inconvenience.

Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546)

27-30 May 2001

Go

Filter Results

Displaying Results 1 - 25 of 99
  • Proceedings Congress on Evolutionary Computation 2001

    Publication Year: 2001, Page(s):0_2 - xii
    Request permission for commercial reuse | PDF file iconPDF (850 KB)
    Freely Available from IEEE
  • Author index

    Publication Year: 2001, Page(s):AI_1 - AI_5
    Request permission for commercial reuse | PDF file iconPDF (218 KB)
    Freely Available from IEEE
  • Self-organized criticality and mass extinction in evolutionary algorithms

    Publication Year: 2001, Page(s):1155 - 1161 vol. 2
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (536 KB) | HTML iconHTML

    The gaps in the fossil record gave rise to the hypothesis that evolution proceeded in long periods of stasis, which alternated with occasional, rapid changes that yielded evolutionary progress. One mechanism that could cause these punctuated bursts is the recolonization of changing and deserted niches after mass extinction events. Furthermore, paleontological studies have shown that there is a pow... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Visualization of EC landscape to accelerate EC conversion and evaluation of its effect

    Publication Year: 2001, Page(s):880 - 886 vol. 2
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (600 KB) | HTML iconHTML

    We evaluate how visualization of an evolutionary computation (EC) landscape is effective using a geophysical task. This technique allows us to actively participate in EC optimization by viewing the distribution of searching points on 2D space mapped from an n-D EC landscape, and indicating where in the EC is the possible global optimum. We construct a Visualized GA system that includes self-organi... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Supervised and unsupervised data mining with an evolutionary algorithm

    Publication Year: 2001, Page(s):767 - 774 vol. 2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (680 KB) | HTML iconHTML

    This paper describes our current research with RAGA (Rule Acquisition with a Genetic Algorithm). RAGA is a genetic algorithm and genetic programming hybrid that is designed for the tasks of supervised and certain types of unsupervised data mining. Since its initial release we have improved its predictive accuracy and data coverage, as well as its ability to generate more scalable rule hierarchies.... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Niche evolution strategy for global optimization

    Publication Year: 2001, Page(s):1086 - 1092 vol. 2
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (572 KB) | HTML iconHTML

    Many real-world problems can be formulated as global optimization problems. In recent years, evolutionary computation has been successfully applied in many such practical optimization problems which are hard to solve using traditional approaches due to their analytical intractability. However, practitioners are always in need of more effective and robust evolutionary algorithms as real-world probl... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Application of evolutionary computation and neural network hybrids for breast cancer classification using mammogram and history data

    Publication Year: 2001, Page(s):1147 - 1154 vol. 2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (664 KB) | HTML iconHTML

    Mammography is the modality of choice for the early detection of breast cancer, primarily because of its sensitivity to the detection of breast cancer. However, because of its high rate of false positive predictions, a large number of biopsies of benign lesions result. The paper explores the use and evaluates the performance of two neural network hybrids as an aid to radiologists in avoiding biops... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Enzyme genetic programming

    Publication Year: 2001, Page(s):1183 - 1190 vol. 2
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (744 KB) | HTML iconHTML

    The work reported in the paper follows from the hypothesis that better performance in certain domains of artificial evolution can be achieved by adhering more closely to the features that make natural evolution effective within biological systems. An important issue in evolutionary computation is the choice of solution representation. Genetic programming, whilst borrowing from biology in the evolu... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • When sharing fails

    Publication Year: 2001, Page(s):873 - 879 vol. 2
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (452 KB) | HTML iconHTML

    Sharing, introduced by D.E. Goldberg and J. Richardson (1987), is probably one of the most investigated ideas for multimodal optimization. Empirical tests have indicated that sharing is capable of maintaining multiple peaks located simultaneously, a feature that allows a final human selection among the found solutions. The author presents a theoretical argument regarding the performance of sharing... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An evolutionary multi-objective local selection algorithm for customer targeting

    Publication Year: 2001, Page(s):759 - 766 vol. 2
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (700 KB) | HTML iconHTML

    In an increasingly competitive marketplace, one of the most interesting and challenging problems is how to identify and profile customers who are most likely to be interested in new products or services. At the same time, minimizing the number of variables used in the prediction task is important with large databases. We consider a novel application of evolutionary multi-objective algorithms for c... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A schema theory analysis of mutation size biases in genetic programming with linear representations

    Publication Year: 2001, Page(s):1078 - 1085 vol. 2
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (636 KB) | HTML iconHTML

    Understanding operator bias in evolutionary computation is important because it is possible for the operator's biases to work against the intended biases induced by the fitness function. Developments in genetic programming (GP) schema theory can be used to better understand the biases induced by the standard subtree crossover when GP is applied to variable-length linear structures. In this paper, ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Parental population sizing in evolutionary strategies

    Publication Year: 2001, Page(s):1351 - 1358 vol. 2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (540 KB)

    One of the major differences of evolution strategies (ES) from other evolutionary computation (EC) is self-awareness of the distinction between parental and offspring populations. This feature is all the more prominent when it comes to the availability of two ES variants: COMMA and PLUS ES (i.e. (μ, λ) and (μ+λ) ES). Even though these two schemes capture, respectively, the anti... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fitness evaluation for nurse scheduling problems

    Publication Year: 2001, Page(s):1139 - 1146 vol. 2
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (732 KB) | HTML iconHTML

    When applying evolutionary algorithms to difficult real-world problems, the fitness function routinely needs evaluating for a very high number of intermediary cases. The paper is concerned with real-world nurse rostering problems with highly constrained resources. We consider a particular approach, which allows for a quick evaluation and is general enough to deal with other kinds of resource plann... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Learning with the molecular-based hypernetwork model

    Publication Year: 2001, Page(s):1177 - 1182 vol. 2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (388 KB) | HTML iconHTML

    The hypernetwork model is a hierarchical architecture that has a representation of the molecular, cellular, and organismic levels of biological organization. It influences flow within each level, and through levels, forming dynamic networks of molecular interactions. With its molecular variation-selection learning algorithm, the hypernetwork is able to solve fairly complex tasks such as the (4-10)... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Genetic programming of polynomial harmonic models using the discrete Fourier transform

    Publication Year: 2001, Page(s):902 - 909 vol. 2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (724 KB) | HTML iconHTML

    The paper presents a genetic programming (GP) system that evolves polynomial harmonic networks. The hybrid tree-structured network representation suggests that terminal harmonics with non-multiple frequencies may enter polynomial function nodes as variables. The harmonics with non-multiple, irregular frequencies are derived analytically using the discrete Fourier transform. The development of poly... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Evolving bipedal locomotion with genetic programming - a preliminary report

    Publication Year: 2001, Page(s):1025 - 1032 vol. 2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (720 KB) | HTML iconHTML

    Shows how genetic programming can be applied to the task of evolving the neural oscillators that produce the coordinated movements of human-like bipedal locomotion. In biomechanical engineering research, robotics and neurophysiology, it is of major interest to clarify the mechanism of human bipedal walking. This serves as the basis for developing several applications, such as rehabilitation tools ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A GA-based fuzzy traffic simulation for crossroad management

    Publication Year: 2001, Page(s):1289 - 1295 vol. 2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (488 KB) | HTML iconHTML

    Conventional fuzzy traffic controllers use membership functions given by human operators. However, this approach does not guarantee the optimal solution to design fuzzy control systems. To find near optimal fuzzy membership functions, we perform traffic simulations by using genetic algorithms. However, it is not easy in traffic control to define a fitness function as a mathematical expression. Thu... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Texture detection by genetic programming

    Publication Year: 2001, Page(s):867 - 872 vol. 2
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (548 KB) | HTML iconHTML

    This paper presents an approach to blind texture detection in images based on adaptation of the 2D-lookup algorithm by genetic programming. The task of blind texture detection is to separate textured regions of an image from non-textured (as e.g. homogeneous) ones, without any reference to a priori knowledge about image content. The 2D-lookup algorithm, which generalizes the well-known co-occurren... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Heuristic operators, redundant mapping and other issues in genetic algorithms

    Publication Year: 2001, Page(s):1398 - 1405 vol. 2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (644 KB) | HTML iconHTML

    This paper uses the 0-1 knapsack problems (KPs) to investigate such issues as early convergence, exploration versus exploitation, redundant mapping and the role of heuristic operators etc. in genetic algorithms (GAs) with the (μ+λ)-strategy. We use the order-based representation for chromosome and propose two different decoding approaches, order-decoding (preserving redundancy) and cycle... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems

    Publication Year: 2001, Page(s):971 - 978 vol. 2
    Cited by:  Papers (116)  |  Patents (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (588 KB) | HTML iconHTML

    The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as multi-objective optimization problems (MOPs)) has attracted much attention. Being population based approaches, EAs offer a means to find a group of Pareto-optimal solutions in a single run. Differential evolution (DE) is an EA that was developed to handle optimization problems over continuous domains. The... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Rule extraction by genetic algorithms based on a simplified RBF neural network

    Publication Year: 2001, Page(s):753 - 758 vol. 2
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (432 KB) | HTML iconHTML

    As an important task of data mining, extracting rules to represent the concept of numerical data is attracting much attention. We propose a novel algorithm to extract rules using genetic algorithms (GA) and the radial basis function (RBF) neural network classifier. The interval for each input in the condition part of each rule is adjusted using GA. The fitness of a chromosome is determined by the ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Representing classification problems in genetic programming

    Publication Year: 2001, Page(s):1070 - 1077 vol. 2
    Cited by:  Papers (60)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (684 KB) | HTML iconHTML

    Five alternative methods are proposed to perform multi-class classification tasks using genetic programming. These methods are: (1) binary decomposition, in which the problem is decomposed into a set of binary problems and standard genetic programming methods are applied; (2) static range selection, where the set of real values returned by a genetic program is divided into class boundaries using a... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An adaptive evolutional neuro learning method using genetic search and extraction of rules from trained networks

    Publication Year: 2001, Page(s):1343 - 1350 vol. 2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (616 KB) | HTML iconHTML

    BP learning is widely known to perform good classification for given training data. However, there is a kind of noise or inconsistent knowledge in training cases. In this case, a neural network will not converge. To avoid such a problem, we propose an adaptive evolutional neuro learning method to handle a subset of the complete set of training cases. This method has a sufficient adaptive ability l... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Why co-evolution beats temporal difference learning at Backgammon for a linear architecture, but not a non-linear architecture

    Publication Year: 2001, Page(s):1003 - 1010 vol. 2
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (716 KB) | HTML iconHTML

    No Free Lunch theorems show that the algorithm must suit the problem. This does not answer the novice's question: for a given problem, which algorithm to use? This paper compares co-evolutionary learning and temporal difference learning on the game of Backgammon, which (like many real-world tasks) has an element of random uncertainty. Unfortunately, to fully evaluate a single strategy using undire... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Collaborative evolutionary multi-project resource scheduling

    Publication Year: 2001, Page(s):1131 - 1138 vol. 2
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (996 KB) | HTML iconHTML

    Large, real-world resource constrained multiple-project scheduling problems involve complex quality criteria. Clearly, issues such as meeting resource constraints, and minimising slippage, flow-time and tardiness are all appropriate and will be applied in such cases. However, often crucial criteria exist which are difficult or impossible to formalise. Since such large projects span multiple resour... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.