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Minimizing the total completion time on a single batch processing machine with non-identical job sizes using ant colony optimization

This paper aims at minimizing the total completion time for a single batch processing machine (BPM) with non-identical job sizes. For this problem, each job has a corresponding processing time and size. The machine can process the jobs in batches as long as the total size of all the jobs in a batch does not exceed the machine capacity. The processing time of a batch is equal to the longest processing time among all the jobs in that batch. This problem is NP-hard and hence an ant colony optimization (ACO) approach based on job sequence is proposed. Random instances were used to test the effectiveness of the proposed approach. Computational results show that ACO significantly outperforms other algorithms addressed in the literature.