量子遗传算法在目标分配上的应用

量子遗传算法是量子计算和遗传算法相结合的产物,量子遗传算法将量子比特和量子门表示引入到遗传算法中,具有比遗传算法更好的搜索效率和收敛性.目标分配问题是一种典型的NP难问题,传统的方法在求解此问题时很容易陷入局部最优.本文利用量子遗传算有效地解决了目标分配最优化的问题,数值模拟表明量子遗传算法在该类问题中具有效性和可行性.

Application of Quantum Genetic Algorithm on the Goal Distribution

Quantum genetic algorithm(QGA) is based on quantum computation and genetic algorithm.QGA has better search ability and quicker convergence speed since it introduce qubit and quantum rotation gate into GA.object assignment problem is a typical NP hard problem,however,the solution of Goal distribution is not satisfying usually.For example it may be stuck at a local optimum.With the powerful searching ability of QGA,object assignment problem can be solved.The numerical simulation shows that QGA is efficient and practical in this field.