Abstract: According to the characteristics of multi-equipment parallel operation and the requirements of efficient operation in four-way-shuttle based storage and retrieval system,an Improved Ant Colony and Greedy Algorithm(IACGA)was proposed to optimize the model of storage allocation,which considered the factors of storage and retrieval efficiency,shelf stability,job balance and goods correlation.The global optimization ability of ant colony algorithm and the local optimization ability of greedy algorithm were combined and the heuristic function,the state transition strategy and the pheromone update rule were improved in the proposed algorithm.The optimization of the main parameters and the effectiveness of the proposed algorithm were verified by simulation experiments.Compared with the standard genetic algorithm,the traditional ant colony algorithm and the shuffled frog leading algorithm,the proposed ant colony-greedy algorithm has better results and more reasonable cargo allocation,and the advantage of the algorithm becomes more obvious as the quantity of goods increases.

Key words: four-way-shuttle based storage and retrieval system, storage allocation, ant colony algorithm, greedy algorithm

摘要： 针对四向穿梭车仓储系统中多设备并行作业特点和高效作业的需求,建立了综合考虑出入库效率、货架稳定性、作业均衡度和货物关联性4个因素的货位分配优化模型,并提出一种改进蚁群贪婪算法(IACGA)的两阶段混合算法对模型进行优化求解。该算法综合了蚁群算法的全局寻优能力与贪婪算法的局部优化调整能力,改进了蚁群算法的启发式函数、状态转移策略以及信息素更新规则。通过仿真实验优化了算法的主要参数,验证了算法的有效性。与标准遗传算法、传统蚁群算法和混合蛙跳算法相比,提出的改进蚁群贪婪算法求解结果更好,货位分配更加合理,且当货物数量越多时,算法优势越明显。

关键词: 四向穿梭车仓储系统, 货位分配, 蚁群算法, 贪婪算法