An ant colony optimization algorithm for the redundancy allocation problem (RAP)

This paper uses an ant colony meta-heuristic optimization method to solve the redundancy allocation problem (RAP). The RAP is a well known NP-hard problem which has been the subject of much prior work, generally in a restricted form where each subsystem must consist of identical components in parall...

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Bibliographic Details
Published in:IEEE transactions on reliability 2004-09, Vol.53 (3), p.417-423
Main Authors: Yun-Chia Liang, Smith, A.E.
Format: Article
Language:English
Subjects:
Ant colony optimization
Associate members
Concurrent computing
Cost function
Genetic algorithms
NP-hard problem
Optimization algorithms
Optimization methods
Redundancy
Reliability
Studies
Testing
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Summary:This paper uses an ant colony meta-heuristic optimization method to solve the redundancy allocation problem (RAP). The RAP is a well known NP-hard problem which has been the subject of much prior work, generally in a restricted form where each subsystem must consist of identical components in parallel to make computations tractable. Meta-heuristic methods overcome this limitation, and offer a practical way to solve large instances of the relaxed RAP where different components can be placed in parallel. The ant colony method has not yet been used in reliability design, yet it is a method that is expressly designed for combinatorial problems with a neighborhood structure, as in the case of the RAP. An ant colony optimization algorithm for the RAP is devised & tested on a well-known suite of problems from the literature. It is shown that the ant colony method performs with little variability over problem instance or random number seed. It is competitive with the best-known heuristics for redundancy allocation.
ISSN:0018-9529
1558-1721
DOI:10.1109/TR.2004.832816