Abstract
AbstractA scheduling problem for a two-stage flexible flow shop with s-batching machines is considered. A batch is a group of jobs that are processed at the same time on a single machine. A maximum batch size is given. The jobs belong to incompatible families. Only jobs of the same family can be batched together. A setup time occurs between different batches. The processing time of a batch is the sum of the processing times of the jobs forming the batch, i.e., the jobs are processed in a serial manner. Batch availability is assumed. Each job has a weight, a due date, and a release date. The performance measure is the total weighted tardiness (TWT). An iterative decomposition approach (IDA) is proposed that uses a grouping genetic algorithm (GGA) or an iterated local search (ILS) scheme to solve the single-stage subproblems. Results of computational experiments based on randomly generated problem instances demonstrate that the IDA hybridized with ILS is able to determine high-quality solutions.KeywordsFlow shops-batchingDecompositionIterated local searchGrouping genetic algorithm
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