针对智能立体仓库货位分配问题,提出一种基于精英多策略的货位分配优化方法.首先,考虑货物重量、出入库频率和出入库时间等因素,以货架重心低、出入库频率高、货物离出入库口近等为原则建立货位分配优化模型;然后,提出一种精英多策略差分进化算法,通过提取部分精英个体的信息指导变异,并根据精英个体的拥挤度变化对不同的阶段使用不同的策略,从而产生高质量的解,同时加快算法的收敛速度;最后,通过10个经典测试函数验证了所提算法的有效性,并基于该方法对某智能制造企业的成品库进行了优化,得到了满意的货位分配方案.%To address the problem of storage location assignment in the intelligent stereoscopic warehouse,a storage location assignment optimization method using elite multi-strategy was proposed.Firstly,by considering the factors of the weight,the frequency and time of import and export of goods,the storage location assignment optimization model was constructed based on the principle of low gravity center of goods shelf,high frequency of import and export and close distance between goods and import and export.Then,an elite multi-strategy-based differential evolution algorithm was designed to solve the constructed model.In this approach,the information of some elite individuals is extracted to guide the mutation and the mutation strategies for different search stages are selected according to the variation of the crowding degree of the elite individuals.Thus,the individuals with high quality are generated and the convergence speed is improved.Finally,the performance of the proposed algorithm was verified over ten classical benchmark functions,and the optimum storage location assignment scheme of the finished product warehouse of a company was obtained by the proposed method.
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