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Robustness of ant colony optimization to noise
Tobias Friedrich
, Timo Kötzing
, Martin S. Krejca
,
Andrew M. Sutton
Computer Science (Duluth)
Research output
:
Contribution to journal
›
Article
›
peer-review
29
Scopus citations
Overview
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Dive into the research topics of 'Robustness of ant colony optimization to noise'. Together they form a unique fingerprint.
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Mathematics
Boolean Function
100%
Combinatorial Problem
100%
Linear Function
100%
Random Noise
100%
Search Space
100%
Variance
100%
Keyphrases
Additive White Gaussian Noise
16%
Ant Colony Optimization
100%
Combinatorial Problems
16%
Fitness Function
16%
Large Noise
33%
Linear Function
16%
Noise Distribution
16%
Noise Model
16%
Noisy-OR
16%
Pathfinding
16%
Pseudo-Boolean Function
16%
Search Space Optimization
16%
Small Noise
16%
Uncertain Environment
16%
Computer Science
Ant Colony Optimization
100%
Boolean Function
16%
Classical Case
16%
Combinatorial Problem
16%
Fitness Function
16%
Gaussian White Noise
16%
Linear Function
16%
Optimization Algorithm
50%
Search Space
16%
Engineering
Ant Colony Optimization
100%
Boolean Function
16%
Fitness Function
16%
Gaussian White Noise
16%
Linear Function
16%
Noise Distribution
16%
Search Space
16%