关键词: 出库货位优化, 出库代价, 货物剩余价值率, 自适应优化权重, 改进遗传算法

Abstract:

Most of the current research on outbound slotting optimization considers the production date of the goods, which is simply to use the first-in first-out principle. How to consider the impact of the production date of the goods on outbound slotting optimization more reasonably is an urgent problem to be solved. For this problem, this paper proposes a outbound slotting optimization model that uses the cost of outbound and the ratio of surplus value of goods as the model factors, and using improved genetic algorithm based on adaptive operator, elite strategy and catastrophe operator with adaptive optimization weights based on warehouse busyness to solve the model. Finally, the actual enterprise production data is used to verify the case. The results show that the improved genetic algorithm is better for the outbound slotting optimization algorithm, and adaptive optimization weights can effectively reduce the risk of goods being damaged or their value falling due to long-term storage and at the same time, it can give priority to outbound efficiency when the warehouse is busy.

Key words: outbound slotting optimization, cost of outbound, the ratio of surplus value of goods, adaptive optimization weights, improved genetic algorithm