基于混合遗传算法的堆垛机路径优化研究

Research on Path Optimization of Stacker Cranes in Automated Stereo Warehouse

针对自动化立体仓库中堆垛机运行路径杂乱的问题,研究了一种基于遗传算法和蚁群算法相结合的混合遗传算法。设计和构建了立体仓库的整体运行模型,并对仓库中的运行区域进行了划分,实现了区域的合理分配。通过新的混合遗传算法,实现了对堆垛机控制算法的优化。通过实验计算,证明了在利用混合遗传算法控制堆垛机存取货物时,堆垛机行走的路程要比使用遗传算法时更加优秀,混合遗传算法能够将路径优化7%左右,因此混合遗传算法满足优化条件。

A hybrid genetic algorithm based on the combination of genetic algorithm and ant colony algorithm is studied for the problem of chaotic operation path of stacker cranes in the automated stereo warehouse.The overall operation model of the three-dimensional warehouse is designed and constructed,and the operation areas in the warehouse are divided to achieve a reasonable allocation of areas.The optimization of the control algorithm of the stacker crane was achieved by means of a new hybrid genetic algorithm.Through experimental calculations,it was demonstrated that when controlling the stacker crane to access the goods using the hybrid genetic algorithm,the distance traveled by the stacker crane was better than when using the genetic algorithm,and the hybrid genetic algorithm was able to optimize the path by about 7%,so the hybrid genetic algorithm satisfies the optimization conditions.