Abstract
An improved quantum genetic algorithm (IQGA) is proposed to avoid declining of the searching ability for multi-peak function optimization and multi-genes chromosome encoding problem. Improvements include adjusting initialization way of chromosome's genes, changing elitist strategy and introducing partial population disaster strategy. Experimental results on continuous multi-peak function optimization and actual nutritional diet optimization show that IQGA is superior to traditional quantum genetic algorithm on convergence speed and global optimization ability. Even for multi-genes encoding problem, this improved quantum genetic algorithm still has higher searching capability, usability and robustness than traditional quantum genetic algorithm.