基于改进遗传算法优化堆垛机速度曲线研究

Research on optimizing the speed curve of stacker based on improved genetic

堆垛机是起重运输行业的重要设备,其在计算机系统的控制下,通过轨道在立体仓库里高效、绿色地往返穿梭,精确停在指位置并存取货物。堆垛机以最短时间从静止状态提升至高速运动状态,在保持一段时间后逐渐减速直至停止,由于受到本身结构的影响,堆垛机以何种速度运行成为目前需要解决的问题。文中提出用速度曲线表示堆垛机的运动特性,并对其进行优化研究。传统的速度曲线优化对目标函数有较强的依赖性和严格性,基于权重分析法(AHP)得到堆垛机关键性能指标的权重,提出改进遗传算法(GA)对速度曲线进行优化。仿真结果表明:该算法具有优化精度高、鲁棒性好的优点,在该领域具有良好的参考意义和实用价值。

As an important equipment in the lifting and transportation industry,under the control of the computer system,the stacker shuttles back and forth in the stereoscopic warehouse efficiently and environmentally on its track,stops at the designated position accurately and stores and picks up goods.The stacker can enter into the high-speed motion state in the shortest time from the static state,and then gradually decelerates until it stops after maintaining for a period of time.Due to the influence of its structure,the speed operation of the stacker has become a problem needs to be solved at present.In this paper,the velocity curve was proposed to represent the motion characteristics of the stacker and optimization study was carried out.However,the traditional speed curve optimization has strong dependence and high requirements on the objective function.Based on the weight analysis method(AHP),the weights of the key performance indexes of the stacker were obtained,and an improved genetic algorithm(GA)was proposed to optimize the speed curve.The simulation results show that the algorithm has the advantages of high optimization accuracy and good robustness,and has good reference significance and practical value in this field.