Concerns about environmental degradation and fossil fuel depletion have led to the advent of energy-aware manufacturing and material handling processes in factories and warehouses. However, as the transition to eco-friendly material handling by electric material handling vehicles (EMV) is progressing, the use of electric forklifts (EFs) remains a challenge, as these EMVs are recognized only as energy consumers. In this paper, we develop an integrated dynamic algorithm for solving the EF routing problem with battery charging constraints in which EFs’ picking or put-away routes, EFs’ battery charging schedules, and the number of EFs operated are simultaneously determined while considering electricity consumption in a warehouse. Time series of electricity-usage penalty estimated by predicted energy consumption in a warehouse facility and equipment level play key roles in establishing EF battery charging schedules. Dynamic models for the arrival processes in material handling and EF battery charging jobs in multiple EF queues are developed and implemented as core engines in the proposed dynamic control algorithm. Operational performance and energy performance of the proposed dynamic algorithm are examined using real energy and operational parameters of the Toyota 9BRU23/16.5 reach truck and compared to those of the metaheuristic approach, called adaptive large neighborhood search. Experimental results of large-size instances with uniformly distributed job locations show that an average 5.6% better performance is achieved by the proposed dynamic algorithm. An additional experiment with the proposed approach and clustered job locations results in 8.9% lower energy-related costs and 1.2% shorter EF travel distances, demonstrating the competitiveness of the proposed energy-aware EF operations strategy for warehouse administration.

对环境退化和化石燃料枯竭的担忧导致了工厂和仓库中对能源敏感的制造和材料处理过程的问世。但是，随着电动材料搬运车（EMV）向环保材料搬运的过渡不断发展，电动叉车（EFs）的使用仍然是一个挑战，因为这些EMV仅被视为能源消耗者。在本文中，我们开发了一种集成的动态算法来解决带有电池充电约束的EF路由问题，其中在考虑电耗的同时确定EF的选择或上架路线，EF的电池充电时间表以及操作的EF数量在仓库里。根据仓库设施和设备级别的预计能耗估算的用电惩罚的时间序列在建立EF电池充电时间表中起着关键作用。在所提出的动态控制算法中，针对多个EF队列中的物料搬运和EF电池充电作业中到达过程的动态模型已开发并实现为核心引擎。使用丰田9BRU23 / 16.5轻便型卡车的实际能量和操作参数检查了所提出的动态算法的操作性能和能量性能，并与称为启发式大邻域搜索的元启发式方法进行了比较。具有均匀分布的作业位置的大型实例的实验结果表明，所提出的动态算法平均可以提高5.6％的性能。