基于改进A^(*)算法的车间物料配送路径规划

Workshop Material Distribution Path Planning Based on Improved A^(*)Algorithm

针对传统避障搜索算法在车间物料配送中仅能解决单点配送且未充分考虑多点配送及往返取货需求的问题,提出一种结合遗传算法优化的A^(*)算法.该方法利用A^(*)算法的成本计算方式完成有障碍物条件下各配送点之间的成本计算,并融合遗传算法的迭代寻优特性,实现了对多点配送及往返取货需求的高效稳定全局搜索.通过某车间物料配送的实际算例验证,该改进算法能有效规划障碍环境下的配送路径,显著提升配送效率.

Aiming at the problem that traditional obstacle avoidance search algorithms could only solve single-point distribution and inadequately considered the needs for multi-point distribution and round-trip pickups in workshop material distribution,we proposed an A^(*)algorithm that combined a genetic algorithm optimization.This method employed the cost calculation approach of the A^(*)algorithm to complete cost calculation between various distribution points under obstacle conditions,and integrated the iterative optimization characteristics of the genetic algorithm to achieve efficient and stable global search for multi-point distribution and round-trip pickup requirements.Through the verification of a practical example of material distribution in a certain workshop,the improved algorithm can effectively plan distribution paths in obstacle environments and significantly improve distribution efficiency.