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5,335
Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion and Generalization
, 1993
"... The paper describes a rank-based fitness assignment method for Multiple Objective Genetic Algorithms (MOGAs). Conventional niche formation methods are extended to this class of multimodal problems and theory for setting the niche size is presented. The fitness assignment method is then modified to a ..."
Abstract
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Cited by 633 (15 self)
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to allow direct intervention of an external decision maker (DM). Finally, the MOGA is generalised further: the genetic algorithm is seen as the optimizing element of a multiobjective optimization loop, which also comprises the DM. It is the interaction between the two that leads to the determination of a
Genetic Programming
, 1997
"... Introduction Genetic programming is a domain-independent problem-solving approach in which computer programs are evolved to solve, or approximately solve, problems. Genetic programming is based on the Darwinian principle of reproduction and survival of the fittest and analogs of naturally occurring ..."
Abstract
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Cited by 1056 (12 self)
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genetic operations such as crossover (sexual recombination) and mutation. John Holland's pioneering Adaptation in Natural and Artificial Systems (1975) described how an analog of the evolutionary process can be applied to solving mathematical problems and engineering optimization problems using what
Software pipelining: An effective scheduling technique for VLIW machines
, 1988
"... This paper shows that software pipelining is an effective and viable scheduling technique for VLIW processors. In software pipelining, iterations of a loop in the source program are continuously initiated at constant intervals, before the preceding iterations complete. The advantage of software pipe ..."
Abstract
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Cited by 581 (3 self)
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pipelining is that optimal performance can be achieved with compact object code. This paper extends previous results of software pipelining in two ways: First, this paper shows that by using an im-proved algorithm, near-optimal performance can be obtained without specialized hardware. Second, we propose a
Adaptive Display Algorithm for Interactive Frame Rates During Visualization of Complex Virtual Environments
, 1993
"... We describe an adaptive display algorithm for interactive frame rates during visualization of very complex virtual environments. The algorithm relies upon a hierarchical model representation in which objects are described at multiple levels of detail and can be drawn with various rendering algorithm ..."
Abstract
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Cited by 450 (10 self)
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We describe an adaptive display algorithm for interactive frame rates during visualization of very complex virtual environments. The algorithm relies upon a hierarchical model representation in which objects are described at multiple levels of detail and can be drawn with various rendering
Optimizing Hierarchical Menus by Genetic Algorithm and Simulated Annealing
"... ABSTRACT Hierarchical menus are now ubiquitous. The performance of the menu depends on many factors: structure, layout, colors and so on. There has been extensive research on novel menus, but there has been little work on improving performance by optimizing the menu's structure. This paper pro ..."
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proposes algorithms based on the genetic algorithm (GA) and the simulated annealing (SA) for optimizing the performance of menus. The algorithms aim to minimize the average selection time of menu items by considering the user's pointer movement and search/decision time. We will show the experimental
Probabilistic Approximation of Metric Spaces and its Algorithmic Applications
- In 37th Annual Symposium on Foundations of Computer Science
, 1996
"... The goal of approximating metric spaces by more simple metric spaces has led to the notion of graph spanners [PU89, PS89] and to low-distortion embeddings in low-dimensional spaces [LLR94], having many algorithmic applications. This paper provides a novel technique for the analysis of randomized ..."
Abstract
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Cited by 351 (32 self)
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. We prove that any metric space can be probabilistically-approximated by hierarchically well-separated trees (HST) with a polylogarithmic distortion. These metric spaces are "simple" as being: (1) tree metrics. (2) natural for applying a divide-and-conquer algorithmic approach
An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1993
"... A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices. Cl ..."
Abstract
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Cited by 360 (0 self)
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. Clustering is achieved by removing arcs of G to form mutually exclusive subgraphs such that the largest inter-subgraph maximum flow is minimized. For graphs of moderate size (- 2000 vertices), the optimal solution is obtained through partitioning a flow and cut equivalent tree of 6, which can be efficiently
Self-organisation in a perceptual network
- IEEE Computer
, 1988
"... young animal or child perceives and identifies features in its envi-, roument in an apparently effortless way. No presently known algorithms even approach this flexible, generalpurpose perceptual capability. Discovering the principles that may underlie perceptual processing is important both for neu ..."
Abstract
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Cited by 364 (0 self)
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young animal or child perceives and identifies features in its envi-, roument in an apparently effortless way. No presently known algorithms even approach this flexible, generalpurpose perceptual capability. Discovering the principles that may underlie perceptual processing is important both
Genetic Algorithms for Real Parameter Optimization
- Foundations of Genetic Algorithms
, 1991
"... This paper is concerned with the application of genetic algorithms to optimization problems over several real parameters. It is shown that k-point crossover (for k small relative to the number of parameters) can be viewed as a crossover operation on the vector of parameters plus perturbations of som ..."
Abstract
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Cited by 191 (0 self)
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This paper is concerned with the application of genetic algorithms to optimization problems over several real parameters. It is shown that k-point crossover (for k small relative to the number of parameters) can be viewed as a crossover operation on the vector of parameters plus perturbations
Results 1 - 10
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