Abstract
This chapter introduces a relatively new meta-heuristic for combinatorial optimization, the ant colony. The ant colony algorithm is a multiple solution global optimizer that iterates to find optimal or near optimal solutions. Like its siblings genetic algorithms and simulated annealing, it is inspired by observation of natural systems, in this case, the behavior of ants in foraging for food. Since there are many difficult combinatorial problems in the design of reliable systems, applying new meta-heuristics to this field makes sense. The ant colony approach with its flexibility and exploitation of solution structure is a promising alternative to exact methods, rules of thumb and other meta-heuristics.
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Keywords
- Local Search
- Variable Neighborhood Descent
- Redundancy Allocation Problem
- Pheromone Intensity
- Great Deluge Algorithm
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© 2007 Springer-Verlag Berlin Heidelberg
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Liang, YC., Smith, A.E. (2007). The Ant Colony Paradigm for Reliable Systems Design. In: Levitin, G. (eds) Computational Intelligence in Reliability Engineering. Studies in Computational Intelligence, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37372-8_1
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DOI: https://doi.org/10.1007/978-3-540-37372-8_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37371-1
Online ISBN: 978-3-540-37372-8
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