具終站序列機台之分散彈性零工式排程問題

Abstract

本研究探討生產系統之分散彈性零工式排程(DFJS)與終站序列機台問題，以最小化總延遲時間為目標函數。在此問題情境下，每個工件必須在DFJS系統加工完後，最後進入序列機台加工。 此排程問題分為兩個階段求解，第一階段使用基因演算法求解DFJS問題；第二階段在獲得DFJS排程解之後，發展終站序列機台之排序演算法，考量交期，依據交期的不同來決定工件進入機台之順序。結合過去學者發展之三種基因演算法(Giovanni et al. 2010; Lu et al. 2015; Wu et al. 2015)與本研究提出終站序列機台之排序演算法，發展三種演算法(GA_OP_S、GA_JS_S、GA_IGA_S)。實驗說明終站序列機台利用率低於80%時，GA_OP_S之績效表現優於其他兩種演算法；而在利用率高時，三種演算法結果幾乎相等。結果顯示，機台利用率的高低，會造成演算法間有不同的差異，進而影響最後的解品質。

This research investigates a scheduling problem in a manufacturing system which is a distributed and flexible job-shop (DFJS) with a terminal series workstation. The scheduling objective is to minimize total tardiness. In the context, each job has to go through the DFJS system and finally proceed to the series workstation. The scheduling problems are solved in two stages. First, we use a genetic algorithm (GA) to solve the DFJS scheduling problem. Then, based on the obtained DFJS scheduling results, we develop a scheduling algorithm for the terminal series workstation. Integrating three prior GAs with the proposed scheduling algorithm for the terminal series workstation, we develop three algorithms (called GA_OP_S, GA_JS_S, and GA_IGA_S). Experiments reveal that GA_OP_S outperforms the other two algorithms when the utilization of the terminal series workstation is low (less than 80%). Yet, in the case of high utilization, the three algorithms perform almost equally well.