四向穿梭车系统的提升机调度优化

提升机作为四向穿梭车系统的瓶颈资源，其调度方案的优劣与系统作业效率密切相关。针对提升机的调度问题，提出了一种调度策略。首先，将提升机调度问题转化为含运输时间的柔性作业车间调度问题，并考虑同层任务的执行顺序约束，构建提升机调度数学模型。其次，提出了一种改进型混合遗传算法对模型进行求解，该算法以混合遗传算法为基础，针对混合遗传算法易产生不合法个体导致算法搜索能力下降的问题，提出了一种个体修正方法，以增强算法的搜索能力。最后，采用某农产品冷库的实际数据对模型及改进型混合遗传算法的可行性与有效性进行了验证。结果表明，相比于仓库中实际应用的策略，改进型混合遗传算法可使任务完成时间至少减少24.66%。

Optimization of Lifts Scheduling for Four-Way Shuttle Systems

As the bottleneck resource of the four-way shuttle systems, the performance of lifts scheduling scheme is closely related to the system operational efficiency. A lifts scheduling strategy is proposed for the lifts scheduling problem. First, the lifts scheduling problem is transformed into a flexible job-shop scheduling problem with transportation time, and a mathematical model is constructed considering the constraints of task sequencing on the same tier. Second, an improved hybrid genetic algorithm is proposed to solve the model, which is based on the hybrid genetic algorithm. Since the hybrid genetic algorithm is easy to produce illegal individuals, leading to the decline of the search ability of the algorithm, an individual correction method is proposed to enhance the search ability of the algorithm. Finally, the feasibility and effectiveness of model and improved hybrid genetic algorithm are verified using the actual data of an agricultural product cold store. The results show that the improved hybrid genetic algorithm can save the task completion time by at least 24.66% compared to the actual applied strategy.