Quantum-Inspired Immune Memory Algorithm for Self-Structuring Antenna Optimization

Based on the concept and principle of quantum computing and immune system, a novel optimization technique, called a quantum-inspired immune memory algorithm is proposed to deal with the problem of the optimization of the switches of the self-structuring antenna. In the algorithm, the proposed memory strategy realizes the information transfer between the courses of evolution. Theoretical analysis proves that quantum-inspired immune memory algorithm converges to the global optimum. The feasibility, efficiency and effectiveness of the proposed algorithm for optimization of self-structuring antenna, whose performance is analyzed by the fast moment method(Mom) are examined. The results show that quantum-inspired immune memory algorithm performs much better than the genetic algorithms in terms of the quality of solution and convergence speed. In addition, parameter analysis demonstrates our algorithm has stable performance and is insensitive to the change of parameters.