基于量子进化算法的多轮廓路径优化

Path optimization for multi-contour based on quantum evolutionary algorithm

针对多轮廓样片加工快进路径优化问题,提出一种改进的量子进化算法。算法设计了基于二维量子位概率幅矩阵模型的快进路径编码方法,实现了由该模型引导的全局搜索,能直接生成样片加工的顺序序列,解码效率高;利用多轮廓加工最优子结构的特征,设计了基于动态规划法的个体适应度评价方法;新的动态旋转角的量子更新策略增强了种群的全局搜索能力。通过标准算例仿真和算法对比实验结果,验证了所提算法的可行性和有效性。

To solve the optimization problem of fast forward path for multi-contour processing, an Improved Quantum Evolutionary Algorithm （IQEA） was proposed. The coding method of fast forward path based on two-dimensional Qubit Measurement Model （QMM） was designed, and the global searching guided by QMM was realized to generate the machining sequence of multi-segment. The decoding efficiency was higher in IQEA. By using the optimal sub- structure of multi-contour processing, the evaluation method of individual fitness based on dynamic programming al- gorithm was designed. The global searching ability of population was enhanced by the new dynamic rotation angle in quantum updating strategy. The simulation results and comparative experiments on classic benchmarks demonstra- ted the feasibility and effectiveness of the presented IQEA.