在本研究中，我們研究 n 個可以進行批次加工的工作跟 m 台平行機台的排程問題，這些平行機台的處理時間是不同的，針對不同機台的合適度條件，即是說工作有適合自己加工的機台，在符合的機台環境下，該工作才能加工，另外工作可以集合成批次再進到機台內開始進行加工，我們研究的目標是在找最小化的總完工時間。 為了求出這個問題的最佳解，本研究提出了一個分枝定界的演算法，在本研究的演算法中首先針對每個工作抵達機台的時間作排列，將率先抵達的工作針對每個機台的可用批次位置做分枝，決定工作在合適機台的批次上加工，接著在考慮剩餘的工作進入相同或不同批次時，該如何作規劃。 ;In this research, we research the scheduling problem with n jobs that can be divided into batches and m parallel machines under availability constraint. Due to the eligibility constraint, each jobs has its own recipe, not all m machines can process job’s recipe. And the jobs have the waiting time before the processing, they can process together when their arrival time smaller than the batch’s waiting time. The objective of our scheduling problem is to minimize the total completion time. In order to find the best solution to this problem, this research proposes a branch and bound algorithm. In the algorithm of this study, first, we resort a sequence according to the job ‘s arrival time. The available batch positions of the machines are branched, and we determine whether schedule the job to process on the batch of the machine, and then how to plan the remaining job entering the same or different batches.
