HSAQEA based reliability redundancy optimization for complex system

Complex system reliability function is nonlinear. It is difficult to design a system which is satisfied reliability condition and also has minimum cost. Many intelligent optimization algorithms are used to solve the problem. Many shortcomings still exist such as being trapped into the local optimal solution easily, low convergence efficiency, etc. In this paper, it presents a hybrid simulated annealing quantum evolutionary algorithms (HSAQEA). Adaptive simulated annealing algorithm is embedded in the quantum evolutionary algorithm, and it retains elitist in the evolution in order to accelerate search for efficiency and speed. The presented algorithm is described in detail. The solving strategy is proposed for the problem of complex system reliability optimization. It also analyzes the reliability distribution of bridge connection system. At last, by calculations of the example and comparison with other algorithms, it proves the algorithm has much stronger ability of local search and better search efficiency. It certifies that this method is feasible and valid.