【摘要】 针对多个易燃品仓库的群巡检的智能滑块路径寻优问题,提出贪心遗传混合式路径优化算法,该算法将贪心策略融入到遗传算法操作过程,用作指导遗传选择操作进行搜索。首先建立仓库群巡检目标分配数学模型,其次设计一种基于贪心遗传混合式算法的三维移动巡检系统。对稀土金属库的规模不同的巡检点进行仿真,与常规的遗传算法和粒子群算法相比,平均巡检路径长度减少了15. 2%,对103个巡检点巡检路径长度减少了6. 1%.对1层库41个巡检点、2层库的51个巡检点、33层库的75个巡检点仿真结果表明,该方法避免了遗传算法的早熟问题,无论巡检的收敛速度还是巡检的最短路径均有明显改善。为保证安全,可在危险品大物资仓库推广使用,具有一定的应用价值和安全示范作用。更多还原

【Abstract】 Aim at flammable goods warehouse,a greedy genetic hybrid path optimization algorithm is proposed with Intelligent slider to solve the problem of searching the optimal path of warehouse group.The greedy strategy is integrated into the genetic algorithm,which is used as a guide for genetic selection in this algorithm. Firstly,the mathematical model for the distribution of warehouse inspection target is established. Secondly,a 3 D mobile inspection system based on greedy genetic hybrid algorithm is designed to solve this problem. Next,different scale inspection points of rare earth metal libraries are simulated. Compared with the conventional genetic algorithm and the particle swarm algorithm,the average inspection path length is reduced by 15. 2%,and the inspection path length of 103 inspection points is reduced by 6. 1%. The simulation results of 41 inspection points in the 1 st floor library,51 inspection points in the 2 layer library,and 75 inspection points in the 33 layer library show that the method can avoid the premature convergence,and regarding both the convergence speed of the inspection and the shortest path of the inspection,there is a significant improvement. The method has strong operability and high efficiency. It can be widely used in the warehouse group,which has certain application value and demonstration function for safety.更多还原