Evolutionary Computing - Lecture Notes in Computer Science
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Published By Springer Berlin Heidelberg

9783540604693, 9783540475156

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Specialised recombinative operators for timetabling problems

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_26 ◽

1995 ◽

pp. 75-85 ◽

Cited By ~ 20

Author(s):

Edmund Burke ◽

David Elliman ◽

Rupert Weare

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An evolutionary algorithm for parametric array signal processing

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_35 ◽

1995 ◽

pp. 191-199 ◽

Cited By ~ 3

Author(s):

Dekun Yang ◽

Stuart Flockton

Keyword(s):

Signal Processing ◽

Evolutionary Algorithm ◽

Array Signal Processing ◽

Parametric Array

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Scheduling planned maintenance of the national grid

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_31 ◽

1995 ◽

pp. 132-153 ◽

Cited By ~ 3

Author(s):

W. B. Langdon

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An adaptive poly-parental recombination strategy

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_24 ◽

1995 ◽

pp. 48-61 ◽

Cited By ~ 15

Author(s):

Jim Smith ◽

T. C. Fogarty

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The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_27 ◽

1995 ◽

pp. 86-93 ◽

Cited By ~ 10

Author(s):

Ben Paechter ◽

Andrew Cumming ◽

Henri Luchian

Keyword(s):

Evolutionary Algorithms ◽

Local Search

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Load balancing application of the genetic algorithm in a nonstationary environment

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_37 ◽

1995 ◽

pp. 224-233 ◽

Cited By ~ 2

Author(s):

Frank Vavak ◽

Terence C. Fogarty ◽

Phillip Cheng

Keyword(s):

Genetic Algorithm ◽

Load Balancing

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A multi-objective approach to constrained optimisation of gas supply networks: The COMOGA method

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_33 ◽

1995 ◽

pp. 166-180 ◽

Cited By ~ 50

Author(s):

Patrick D. Surry ◽

Nicholas J. Radcliffe ◽

Ian D. Boyd

Keyword(s):

Supply Networks ◽

Constrained Optimisation ◽

Multi Objective ◽

Gas Supply

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Comparing genetic algorithms, simulated annealing, and stochastic hillclimbing on timetabling problems

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_28 ◽

1995 ◽

pp. 94-102 ◽

Cited By ~ 9

Author(s):

Peter Ross ◽

Dave Corne

Keyword(s):

Genetic Algorithms ◽

Simulated Annealing

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The ant colony metaphor for searching continuous design spaces

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_22 ◽

1995 ◽

pp. 25-39 ◽

Cited By ~ 137

Author(s):

G. Bilchev ◽

I. C. Parmee

Keyword(s):

Ant Colony

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Genetic operators and constraint handling for pipe network optimization

Evolutionary Computing - Lecture Notes in Computer Science ◽

10.1007/3-540-60469-3_32 ◽

1995 ◽

pp. 154-165 ◽

Cited By ~ 6

Author(s):

Dragan A. Savic ◽

Godfrey A. Walters

Keyword(s):

Network Optimization ◽

Constraint Handling ◽

Pipe Network ◽

Genetic Operators

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Evolutionary Computing - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Specialised recombinative operators for timetabling problems

An evolutionary algorithm for parametric array signal processing

Scheduling planned maintenance of the national grid

An adaptive poly-parental recombination strategy

The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms

Load balancing application of the genetic algorithm in a nonstationary environment

A multi-objective approach to constrained optimisation of gas supply networks: The COMOGA method

Comparing genetic algorithms, simulated annealing, and stochastic hillclimbing on timetabling problems

The ant colony metaphor for searching continuous design spaces

Genetic operators and constraint handling for pipe network optimization

Evolutionary Computing - Lecture Notes in Computer Science
Latest Publications