Redundancy allocation problems (RAPs) have attracted much attention for the past thirty years due to its wide applications in improving the reliability of various engineering systems. Because RAP is an NP-hard problem, and exact methods are only applicable to small instances, various heuristic and meta-heuristic methods have been proposed to solve it. In the literature, most studies on RAPs have been conducted for single-level systems. However, real-world engineering systems usually contain multiple levels. In this paper, the RAP on multi-level systems is investigated. A novel memetic algorithm (MA) is proposed to solve this problem. Two genetic operators, namely breadth-first crossover and breadth-first mutation, and a local search method are designed for the MA. Comprehensive experimental studies have shown that the proposed MA outperformed the state-of-the-art approach significantly on two representative examples. © 2010 IEEE.
Bibliographical noteThis work was partially supported by EPSRC Grant EP/D052785/1 on “SEBASE: Software Engineering By Automated Search,” National Natural Science Foundation of China Grant U0835002, and the Fund for Foreign Scholars in University Research and Teaching Programs under Grant B07033. Associate Editor: G. Levitin.
- Evolutionary algorithms
- memetic algorithms
- multi-level systems
- redundancy allocation