A novel parallel quantum genetic algorithm
Gexiang Zhang, Weidong Jin, Laizhao Hu · 2004
We propose a novel parallel evolutionary algorithm called coarse-grained parallel quantum genetic algorithm (CGPQGA). The main points of CGPQGA are that a new chromosome representation called qubit representation, a novel evolutionary strategy called qubit phase comparison approach and an extended version of coarse-grained model called hierarchical ring model are introduced. Based on the concepts and principles of quantum computing and quantum parallelism introduced, CGPQGA is characterized by rapid convergence, good global search capability and the ability of possessing exploration and exploitation simultaneously. In CGPQGA, the best individual can be easy to migrate to all processors and communication overhead is much less expensive. The experimental results of infinite impulse response digital filter design demonstrate that CGPQGA can speedup the migration of the top individuals of subpopulations and CGPQGA is superior to other several genetic algorithms greatly in quality and efficiency.