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Cultural algorithm

Known as: CA, Cultural algorithms 
Cultural algorithms (CA) are a branch of evolutionary computation where there is a knowledge component that is called the belief space in addition to… Expand
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Papers overview

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2017
2017
Inacloudenvironment,computingresourcesareavailabletousers,andtheypayonlyfortheused resources.Task scheduling… Expand
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2015
2015
Abstract Social networks can be viewed as a reflection of the real world which can be studied to gain insight into the real life… Expand
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Highly Cited
2009
Highly Cited
2009
This study presents an evolutionary neural fuzzy network, designed using the functional-link-based neural fuzzy network (FLNFN… Expand
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Highly Cited
2009
Highly Cited
2009
Evolutionary algorithms (EAs) are general-purpose stochastic search methods that use the metaphor of evolution as the key element… Expand
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Highly Cited
2008
Highly Cited
2008
In this paper a computational model of the cultural evolution process is described. This model integrates several traditional… Expand
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Highly Cited
2008
Highly Cited
2008
  • K. Deb
  • Multiobjective Optimization
  • 2008
  • Corpus ID: 19531247
In its current state, evolutionary multiobjective optimization (EMO) is an established field of research and application with… Expand
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Highly Cited
2004
Highly Cited
2004
This paper introduces a cultural algorithm that uses domain knowledge to improve the performance of an evolutionary programming… Expand
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Highly Cited
2004
Highly Cited
2004
  • N. Ho, J. C. Tay
  • Proceedings of the Congress on Evolutionary…
  • 2004
  • Corpus ID: 11600553
This work presents an efficient methodology called GENACE for solving the flexible job-shop scheduling problem (or FJSP) with… Expand
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Highly Cited
1999
Highly Cited
1999
  • X. Jin, R. Reynolds
  • Proceedings of the Congress on Evolutionary…
  • 1999
  • Corpus ID: 61446049
The key idea behind cultural algorithms is to acquire problem solving knowledge (beliefs) from the evolving population and in… Expand
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Highly Cited
1996
Highly Cited
1996
This paper shows how the performance of a genetic programming system can be improved through the addition of mechanisms for… Expand
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