<![CDATA[This research concerns a batch scheduling problem with the process time used in the existing batch scheduling research can vary. One of the factors influencing processing time is machine deterioration and learning-forgetting process. The effect of the deterioration can results in a longer process time due to decreased machine capability, as well as an increase in service life or usage. The effect of the learning process can result in a faster product processing time due to an increase in operator experience in processing the product. Meanwhile, the effect of the forgetting process can result in slower product processing times due to the lag time between processing of the same product. This research proposes a batch scheduling model for a flow shop with a processing tow-item with considering of the deterioration process in Stage One and learning-forgetting process in Stage Two. The objectives is to minimize total actual flow time. The decision variables in this research are number of batch (?), batch size (Qi), and batch processing sequence. The problem-solving method was developed by proposed heuristic algorithms.The proposed algorithm is consist of batching sub algorithm, and sequence sub algorithm. Numerical testing shows that the proposed algorithm is able to solve the problem of a batch scheduling for a flow shop to minimize total actual flow time and the solution obtained by the algorithm is a feasible solution.]]>
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