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134
An Empirical Comparison of Four Initialization Methods for the KMeans Algorithm
, 1999
"... In this paper, we aim to compare empirically four initialization methods for the KMeans algorithm: random, Forgy, MacQueen and Kaufman. Although this algorithm is known for its robustness, it is widely reported in literature that its performance depends upon two key points: initial clustering an ..."
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Cited by 134 (0 self)
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In this paper, we aim to compare empirically four initialization methods for the KMeans algorithm: random, Forgy, MacQueen and Kaufman. Although this algorithm is known for its robustness, it is widely reported in literature that its performance depends upon two key points: initial clustering and instance order. We conduct a series of experiments to draw up (in terms of mean, maximum, minimum and standard deviation) the probability distribution of the squareerror values of the final clusters returned by the KMeans algorithm independently on any initial clustering and on any instance order when each of the four initialization methods is used. The results of our experiments illustrate that the random and the Kaufman initialization methods outperform the rest of the compared methods as they make the KMeans more effective and more independent on initial clustering and on instance order. In addition, we compare the convergence speed of the KMeans algorithm when using each o...
An Overview of Genetic Algorithms: Part 1, Fundamentals
, 1993
"... this article may be reproduced for commercial purposes. 1 Introduction ..."
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Cited by 123 (1 self)
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this article may be reproduced for commercial purposes. 1 Introduction
A Comparison of Genetic Sequencing Operators
 Proceedings of the fourth International Conference on Genetic Algorithms
, 1991
"... This work compares six sequencing operators that have been developed for use with genetic algorithms. An improved version of the edge recombination operator is presented, the concepts of adjacency, order, and position are reviewed in the context of these operators, and results are compared for ..."
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Cited by 107 (4 self)
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This work compares six sequencing operators that have been developed for use with genetic algorithms. An improved version of the edge recombination operator is presented, the concepts of adjacency, order, and position are reviewed in the context of these operators, and results are compared for a 30 city "Blind" Traveling Salesman Problem and a real world warehouse/shipping scheduling application.
VLSI cell placement techniques
 ACM Computing Surveys
, 1991
"... VLSI cell placement problem is known to be NP complete. A wide repertoire of heuristic algorithms exists in the literature for efficiently arranging the logic cells on a VLSI chip. The objective of this paper is to present a comprehensive survey of the various cell placement techniques, with emphasi ..."
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Cited by 93 (0 self)
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VLSI cell placement problem is known to be NP complete. A wide repertoire of heuristic algorithms exists in the literature for efficiently arranging the logic cells on a VLSI chip. The objective of this paper is to present a comprehensive survey of the various cell placement techniques, with emphasis on standard ce11and macro
Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators
 Artificial Intelligence Review
, 1999
"... This paper is the result of a literature study carried out by the authors. It is a review of the dierent attempts made to solve the Travelling Salesman Problem with Genetic Algorithms. We present crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Alg ..."
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Cited by 88 (2 self)
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This paper is the result of a literature study carried out by the authors. It is a review of the dierent attempts made to solve the Travelling Salesman Problem with Genetic Algorithms. We present crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Algorithms with dierent representations such as: binary representation, path representation, adjacency representation, ordinal representation and matrix representation. Likewise, we show the experimental results obtained with dierent standard examples using combination of crossover and mutation operators in relation with path representation. Keywords: Travelling Salesman Problem; Genetic Algorithms; Binary representation; Path representation; Adjacency representation; Ordinal representation; Matrix representation; Hybridation. 1 1 Introduction In nature, there exist many processes which seek a stable state. These processes can be seen as natural optimization processes. Over the last...
Learning Bayesian Network Structures by Searching For the Best Ordering With Genetic Algorithms
 IEEE Transactions on Systems, Man and Cybernetics
, 1996
"... In this paper we present a ne_(l n [!ii ' with respect to Bayesian networks con ogy for inducing Bayesian network structures frop3 titute the roblem of the evidence propagation and a database of cases. The methodology is based oap&lll searching for the best ordering of the system vari th ..."
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Cited by 69 (9 self)
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In this paper we present a ne_(l n [!ii ' with respect to Bayesian networks con ogy for inducing Bayesian network structures frop3 titute the roblem of the evidence propagation and a database of cases. The methodology is based oap&lll searching for the best ordering of the system vari the problem of the model search. The problem of shies by means of genetic algorithl{. Since his th_vidence propagation consists of once the vMproblem of finding an optimal ordea. teeuarue}rables are known, the assignment of resembles the traveling salesman p'FolUleh)ve use .... IW. ....... probablhles to the values of the rest of the van genetic operators that were developed for the latter  problem. The quality of a variable ordering is eval ables. Cooper [4] demonstrated that this problem Mated with the algorithm K2. We present empirical results that were obtained with a simulation of the ALARM network.
Memetic Algorithms for Combinatorial Optimization Problems: Fitness Landscapes and Effective Search Strategies
, 2001
"... ..."
An Indirect Genetic Algorithm for a Nurse Scheduling Problem
 ACCEPTED FOR PUBLICATION BY COMPUTERS AND OPERATIONAL RESEARCH
"... This paper describes a Genetic Algorithms approach to a manpowerscheduling problem arising at a major UK hospital. Although Genetic Algorithms have been successfully used for similar problems in the past, they always had to overcome the limitations of the classical Genetic Algorithms paradigm in ha ..."
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Cited by 47 (12 self)
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This paper describes a Genetic Algorithms approach to a manpowerscheduling problem arising at a major UK hospital. Although Genetic Algorithms have been successfully used for similar problems in the past, they always had to overcome the limitations of the classical Genetic Algorithms paradigm in handling the conflict between objectives and constraints. The approach taken here is to use an indirect coding based on permutations of the nurses, and a heuristic decoder that builds schedules from these permutations. Computational experiments based on 52 weeks of live data are used to evaluate three different decoders with varying levels of intelligence, and four wellknown crossover operators. Results are further enhanced by introducing a hybrid crossover operator and by making use of simple bounds to reduce the size of the solution space. The results reveal that the proposed algorithm is able to find high quality solutions and is both faster and more flexible than a recently published Tabu Search approach.
System Level Performance Analysis  the SymTA/S Approach
 IEE Proceedings Computers and Digital Techniques
, 2005
"... SymTA/S is a systemlevel performance and timing analysis approach based on formal scheduling analysis techniques and symbolic simulation. The tool supports heterogeneous architectures, complex task dependencies and context aware analysis. It determines systemlevel performance data such as endtoe ..."
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Cited by 40 (9 self)
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SymTA/S is a systemlevel performance and timing analysis approach based on formal scheduling analysis techniques and symbolic simulation. The tool supports heterogeneous architectures, complex task dependencies and context aware analysis. It determines systemlevel performance data such as endtoend latencies, bus and processor utilization, and worstcase scheduling scenarios. SymTA/S furthermore combines optimization algorithms with system sensitivity analysis for rapid design space exploration. This paper gives an overview of the current research interests in the SymTA/S project.