基于量子行为粒子群算法的铣削用量优化

铣削加工中如何选择最佳的铣削用量是一个多约束非线性的复杂优化问题。在考虑实际加工约束的情况下,以最小化加工成本为目标,采用量子行为粒子群优化(QPSO)算法对铣削实例进行优化,得出了最优的铣削用量组合。通过与实际使用经验值对比,验证该算法能够有效地优化铣削用量,节约加工成本。

Milling Parameter Optimization Based on Quantum-behaved Particle Swarm Optimization Algorithm

In milling operations,it is a non-linear optimization problem with high complexity and many constraints that is how to select a set of milling parameters.Considering a set of practical machining constraints and with the goal of minimizing production cost,the quantum-behaved particle swarm optimization (QPSO) algorithm was used to optimize a milling example and obtain the optimal milling parameters.Comparing with empirical ones,it is proved that this algorithm can optimize the milling parameters effectively and reduce the production cost.