【 中文摘要 】本发明公开了一种智能仓储环境下的任务调度方法，应用于双深位多层穿梭车储分系统，涉及智能仓储技术领域，该方法包括：获取出库信息；根据出库信息进行种群初始化，得到第一种群；检测迭代次数是否为第一次迭代；根据预设目标函数，将第一种群中的个体划分至不同等级的可支配层，并根据检测结果及个体对应的可支配层，从第一种群中确定第一类个体，使第一类个体进行交叉、变异后，将产生的种群更新为第一种群；当迭代次数达到预设迭代次数时，根据迭代结果确定最佳的货物调度方案。本发明有利于解决双深位系统的阻塞货物重排问题，从而缩短出货时间。

【 英文摘要 】The invention discloses a task scheduling method in an intelligent storage environment, which is applied to a double-deep-position multi-layer shuttle storage subsystem, and relates to the technical field of intelligent storage. The method comprises the following steps of : acquiring delivery information; Performing population initialization according to the delivery information to obtain a first population; Detecting whether the number of iterations is a first iteration; Dividing individuals in the first population into disposable layers of different levels according to a preset objective function, determining a first type of individuals from the first population according to the detection result and the disposable layers corresponding to the individuals, crossing the first type of individuals, and updating the generated population to the first population after mutation; When the number of iterations reaches a preset number of iterations, an optimal cargo scheduling scheme is determined based on the iterations. The present invention is favorable to solving the problem of jamming and rearrangement of goods in double deep position system, and this can shorten the delivery time.

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