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Using Case Retrieval to Seed Genetic Algorithms |
Oman, Stephen; Cunningham, Padraig
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TCD-CS-1997-08 In this paper we evaluate the usefulness of seeding genetic algorithms
(GAs) from a case-base. This is motivated by the expectation that the seeding will
speed up the GA by starting the search in promising regions of the search space. We
evaluate this case-based seeding on popular GA solutions to the Travelling Salesman
Problem (TSP) and the Job-Shop Scheduling Problem (JSSP). We find that seeding
works very well with the TSP but poorly with the JSSP. We have discovered that this
discrepancy may be predicted by examining the correlation of parent and offspring
fitness. In the TSP this correlation is strong and the seeding works well, the converse
is true for the JSSP. This provides a simple mechanism to evaluate the potential for
seeding in genetic algorithms in general.
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Keyword(s):
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Computer Science |
Publication Date:
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1997 |
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Type:
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Report |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Institution:
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Trinity College Dublin |
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Citation(s):
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Oman, Stephen; Cunningham, Padraig. 'Using Case Retrieval to Seed Genetic Algorithms'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-1997-08, 1997, pp12 |
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Publisher(s):
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Trinity College Dublin, Department of Computer Science |
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File Format(s):
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application/pdf |
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First Indexed:
2014-05-13 05:34:52 Last Updated:
2015-04-10 05:14:16 |
