基于量子遗传算法的非线性无约束优化方法

量子遗传算法(QGA)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旋转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。非线性无约束优化是典型的工程应用问题,而复杂非线性函数的优化结果往往不能令人满意,如陷入局部最优等。利用量子遗传算法强大的搜索能力,可以很好的解决复杂非线性函数的无约束优化问题,实验表明量子遗传算法在该类问题中的有效性和可行性。

Nonlinear Optimization without restriction based on Quantum Genetic Algorithm

Quantum Genetic Algorithm 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. Nonlinear optimization without restriction is a typical engineering application, however, the solution of complex nonlinear optimization is usually not satisfying. For example it may be stuck at a local optimum. With the powerful searching ability of QGA, complex nonlinear optimization can be solved Experiment shows that Quantum Genetic Algorithm is efficient and practical in this field.