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考慮執行與延遲時間兩績效下自動倉儲系統動態存取法則之研究

A Study of Dynamic Sequencing of Automated Storage and Retrieval Systems with Considering Performances of Execution and Delay Times

摘要


一般自動倉儲系統只根據某一績效,定出一個較好的存取法則,作為整個倉儲系統沿用的法則;一旦績效改變,將無法再得到較好的表現。本研究提出一套動態法則決策架構,能夠同時兼顧執行與延遲時問兩績效評估,於各個決策點適時提供適當的法則,期使整個倉儲系統能夠有良好的整體績效。此架構,所使用的存取法則包含 FCFS、DNN 與 SDDT 等法則。利用模擬,並結合遺傳演算法找尋較佳存取法則的排列,經由實驗證實使用動態存取法則能兼顧不同績效的表現。

並列摘要


Automated storage and retrieval systems (AS/RSs) usually use a single storage and retrieval (S/R) rule to decide which task should be done first. This approach can not obtain better performance due to lack of adjustment with environment or system changes. In addition, the single rule approach can only obtain the better result for a single performance criterion. This study proposes a different approach which gives an opportunity to dynamically choose a rule from multiple SIR rules when a task decision comes. This research uses the genetic algorithm (GA) approach to develop the dynamic rule which has better performances in both total execution time and total tardiness time. Moreover, this study develops an integrated system which combines a simulation system software with a GA software. The parameters of the simulation model of an AS/RS are studied, namely, number of open storage locations, number of dual commands, number of due-times, and arriving rate of new task. The rules can be chosen are first-come-first-serve (FCFS), dynamic-nearest-neighbor (DNN), and SDDT(Shortest Delivery Due Date).

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