Quantum evolutionary algorithm for multi-objective optimization problems
Gexiang Zhang, Weidong Jin, Laizhao Hu · 2003
In this paper, a novel evolutionary algorithm called new quantum evolutionary algorithm (NQEA) is proposed to solve a class of multi-objective optimization problems. The main point of NQEA is that a new quantum logic rotation gate is introduced. NQEA characterizes rapid convergence, good global search capability and short computing time. Then, the convergence of NQEA is also analyzed using random functional theory. The results from optimization design of IIR digital filters demonstrate that NQEA is superior to other several conventional evolutionary algorithms greatly in quality and efficiency.