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Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach
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DOI：10.1016/0305-0548(95)00056-9.png)
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This paper optimizes a well known NP-hard combinatorial problem-redundancy allocation-using a combined neural network and genetic algorithm (GA) approach. The GA searches for the minimum cost solution by selecting the appropriate components for a series-parallel system, given a minimum system reliability constraint. A neural network is used to estimate the system reliability value during search. This approach is an example of a computationally efficient method to apply GA optimization to problems for which repeated calculation of the objective function is impractical. Copyright (C) 1996 Elsevier Science Ltd
Keyword:
SYSTEM-RELIABILITY
OPTIMIZATION
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