穿梭车仓储系统复合作业路径优化

将入库任务和出库任务进行合理搭配构成复合作业是穿梭车仓储系统常用的作业模式,合理的复合作业路径优化对于提升作业效率,降低作业成本具有重要意义。为提高穿梭车仓储系统的出入库效率,将系统复合作业路径优化归结为任务指派问题,以完成一批拣货任务的总时间最小为目标建立优化模型。设计了一种改进的离散粒子群优化算法,重新定义了粒子的位置和速度及运动方程,将循环交叉和交换变异引入速度的加法运算,实现算法的快速收敛,同时通过排斥算子保持粒子群的多样性,减小算法陷入局部最优的可能性。仿真结果表明,该算法性能优于遗传算法,有效地缩短了复合作业的时间,提高了拣货效率。

Routing Optimization of Compound Operations in Shuttle-Based Storage and Retrieval Systems

It is a common operation mode of shuttle-based storage and retrieval systems(SBS/RS)to combine storage and outbound tasks to form a compound operation.Optimizing a reasonable compound operation path is of great significance for improving operation efficiency and reducing operation costs.In order to improve the order picking efficiency of SBS/RSs,the optimization of the system′s compound operation path is attributed to a task assignment problem,and an optimization model is established with the goal of minimizing the total time to complete a batch of tasks.An improved discrete particle swarm optimization(IDPSO)algorithm is designed.The position and velocity of particles and the equation of motion are redefined.Cycle crossover and exchange mutation are introduced into the addition of velocity to achieve fast convergence of the algorithm,while maintaining the diversity of the particle swarm through a repulsion operator,reducing the possibility of falling into a local optimum.The simulation results show that the performance of the algorithm is better than genetic algorithm,which effectively shortens the time of compound operations and improves the picking efficiency.