Affiliations: School of Electrical Engineering, Southwest Jiaotong
University, Chengdu, Sichuan, 610031, P.R. China. zhgxdylan@126.com | Department of Computer Science, The University of
Sheffield, Regent Court, Portobello Street, Sheffield, S1 4DP, UK.
M.Gheorghe@dcs.shef.ac.uk | Engineering Research Center of Transportation Safety,
Ministry of Education, Wuhan University of Technology, Wuhan, Hubei, 430063,
P.R.China. chaozhongwu@gmail.com
Note: [] Address for correspondence: School of Elect. Engin., Southwest
Jiaotong University, Chengdu, Sichuan, 610031, P.R.China. This work is
supported by the National Natural Science Foundation of China (60702026,
60572143)
Abstract: This paper introduces an evolutionary algorithm which uses the
concepts and principles of the quantum-inspired evolutionary approach and the
hierarchical arrangement of the compartments of a P system. The P system
framework is also used to formally specify this evolutionary algorithm.
Extensive experiments are conducted on a well-known combinatorial optimization
problem, the knapsack problem, to test the effectiveness of the approach. These
experimental results show that this evolutionary algorithm performs better than
quantum-inspired evolutionary algorithms, for certain arrangements of the
compartments of the P system structure utilized.
Keywords: Quantum-inspired evolutionary algorithm, P systems, knapsack problem
