关键词: 群体智能算法, 量子粒子群优化, 细菌觅食算法, 应急选址

Abstract:

In order to solve the problem of prematurity of swarm intelligence algorithm and slow speed of convergence of bacterial forging algorithm, an algorithm is proposed, which fuses quantum particle swarm together with bacteria foraging optimization. After considering the advantages of bacteria foraging optimization, quantum computing theory and particle swarm optimization, the proposed fusion algorithm takes the bacterial foraging algorithm as the main body and embedded quantum evolutionary algorithm and particle swarm optimization algorithm into it, thus improving the performance of the algorithm greatly. Through solving and validating the three criteria functions, the results show that the proposed fusion algorithm improves convergence precision and speed. Finally, the proposed algorithm is used to solve public health emergency service facility location problem and achieves good results, proving its effectiveness.

Key words: swarm intelligence algorithm;quantum particle swarm optimization;bacterial foraging algorithm;emergency service facilities point location