A New Combinatorial Optimal Algorithm Based on QEA

This paper combines quantum evolutionary algorithm with the available evolutionary algorithms, uses quantum computing parallelism to search solution space efficiently, uses the traditional evolutionary algorithm to optimize the result observed by quantum population and then uses the optimized result to guide the generation of some individuals of quantum population. It maintains the population diversity of quantum evolutionary algorithm and avoids premature. Meanwhile it adopts the different evolutionary algorithms to combine with quantum evolutionary algorithm to solve different problems, which will improve the adaptability of algorithm.