It is well known that inventory cost takes up a large proportion of the total cost of logistics and warehousing. Enterprises have been trying to improve and optimize the storage process in the warehouse in order to reduce inventory cost. Based on the study on general stereoscopic warehouses, considering the constraints of forklift load, cargo capacity, and storage strategy, we establish a slotting optimization model whose goal is to achieve a minimum distance of staff walking during storage operation in warehouses. According to the characteristics of the problem and the model, we transform the slotting optimization problem to a two-layered optimization issue: slot selection optimization and slot order optimization. An improved genetic algorithm and a heuristic algorithm are combined to solve the model. Finally, simulation results verify the rationality and feasibility of the model and algorithm, which can be used to solve the problem of slotting optimization of most general warehouses.%在物流仓储的总成本中, 库存成本占很大比重.企业为了减少库存成本, 不断设法去改进和优化仓库"存储"的过程.针对普通立体仓库的入库过程, 在考虑叉车载重、货位容量和存储策略等限制条件下, 建立了以入库作业过程中工作人员行走总路程最小为目标的货位优化模型.根据问题和模型特点, 将货位优化问题分为两层优化:货位选择优化层和货位顺序优化层;然后将传统遗传算法同启发式算法相结合对模型进行求解;最后通过仿真实验验证了模型和算法的合理性和可行性.该成果可用于解决多数普通仓库的货位优化问题.
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