DNA Evolutionary Algorithm for Scheduling a Single Batch-processing Machine with Non-identical Job Sizes

The problem of batch-processing machines with non-identical job sizes is a combination of classical scheduling and batch scheduling. The makespan on a single batch-processing machine with non-identical job sizes is NP-complete. In this paper DNA Evolutionary Algorithm (DEA) is applied to minimize the makespan on a single machine. Four operators of DEA are adopted in the evolution including division、level selection、mutation and vertical selection. The vertical selection operator was redesigned by using the probability-based mechanism to escape local optimum. The solutions produced by the algorithm were divided into batches with Batch First Fit algorithm. In the experiment,all levels of instances were simulated and the results demonstrated the efficiency of the proposed algorithm.