关键词: 立体仓库优化, 大规模货位分配, 遗传算法, 延迟接受爬山算法, 两阶段混合算法

Abstract: To meet the needs of metal processing and equipment manufacturing enterprises for the safety and efficiency of large and heavy-duty automatic warehouses,a multi-objective optimization model for slotting problems was established,which considered the requirements of warehouse entry and exit efficiency,shelf stability,load balance of stackers.For such a model,a two-stage hybrid algorithm that integrated the advantages of Genetic Algorithm (GA) and Late Acceptance Hill-Climbing named GA-LAHC was proposed.Meanwhile,the crossover operator of storage-position greed was designed to enhance the information perception ability of GA and accelerate the convergence speed.The effectiveness and parametric sensitivity of the algorithm were analyzed by simulation experiments.Experimental results showed that the proposed algorithm performed better than PSO,GA,and LAHC in solution stability and accuracy.

Key words: automated warehouse optimization, large-scale slotting optimization, genetic algorithms, late acceptance hill-climbing algorithm, two-stage hybrid algorithm