A Quantum-Inspired Evolutionary Approach for non- Homogeneous Redundancy Allocation in Series- Parallel Multi-State Systems

Abstract : Redundancy allocation is a family of well-known reliability optimization problems. The non-homogeneous type of redundancy allocation in series-parallel multi-state systems is among the most difficult ones. Evolutionary algorithms (EAs) are frequently applied to solve the problem, mainly due to the huge search space and the non-closed-form system reliability. This work proposes an efficient approach that combines a quantum-inspired evolutionary algorithm (QEA) with a newly designed local search strategy. Different from the existing EAs, it is able to evolve an explicit probabilistic model to explore the search space in an iterative way. The proposed method is tested on two benchmark problems with the comparisons to the published results. The results are promising in terms of both solution quality and computation efficiency.
Document type :
Conference papers
Complete list of metadatas

Cited literature [9 references]  Display  Hide  Download

https://hal-supelec.archives-ouvertes.fr/hal-01108136
Contributor : Yanfu Li <>
Submitted on : Thursday, January 22, 2015 - 11:26:36 AM
Last modification on : Sunday, June 24, 2018 - 9:00:48 PM
Long-term archiving on : Thursday, April 23, 2015 - 10:25:42 AM

Files

halupload.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01108136, version 1

Citation

Yan-Fu Li, Enrico Zio. A Quantum-Inspired Evolutionary Approach for non- Homogeneous Redundancy Allocation in Series- Parallel Multi-State Systems. ICRMS 2014, Aug 2014, Guang Zhou, China. ⟨hal-01108136⟩

Share

Metrics

Record views

438

Files downloads

292