A Study of Dynamic Scheduling of Automated Storage/Retrieval Systems

• Main Authors: Jerry Chiang, 姜世川
• Other Authors: Rau, Hsin
• Format: Others
• Language: zh-TW
• Published: 1997
• Online Access: http://ndltd.ncl.edu.tw/handle/99933328772580340840

碩士 === 中原大學 === 工業工程研究所 === 85 === According to our survey, most automated storage and retrieval systems (AS/RSs) use a single storage and retrieval (S/R) rule to decide which task (storage, retrieval, or both; this study handles the latter case, which is called as a dual-command task) should be done first. This approach can not obtain better performance due to lack of adjustment with environment or system changes. Usually, the single rule approach caponly obtain a better result for a single performance criterion. This study proposes a different approach which gives an opportunity to dynamically choose a rule from multiple S/R rules when a task decision comes. This research develops an integrated system which combined a simulation system software with a genetic algorithm (GA) software. The parameters of the simulation model of an AS/RS are studied, namely open storage locations, numbers of dual commands, numbers of due dates, and arriving rate of new task. The rules can be chosen are first-come-first-serve (FCFS), dynamic-nearest-neighbor (DNN), and SDDT-R (Shortest Delivery Due Date-Random). The performance criterion used in this study are total execution time, total tardiness time, and largest queue length, etc. This study identifies results reported in the literature that the approach ofDNN has the shortest total execution time but a poor performance in total tardiness time andthe approach of due-date has the lowest tardiness time but a poor performance in total execution time. Moreover, this study shows that one of the approaches with the multiple rules, GA has the best result for multiple performance criteria. It has the similar performance as DNN in total execution time, but has a better result than DNN in total tardiness time.