A spreadsheet based genetic algorithm model for hybrid flowshop with batch and discrete processors

This paper proposed a spreadsheet based genetic algorithm (SGA) model as a practical approach to solve a complicated hybrid flowshop (HFS) with multiple unrelated batch and discrete processors, stage skipping behavior, setup times, and machine eligibility restrictions. The proposed model is capable to handle three crucial and inter-dependent decisions which include batching, loading and sequencing. The scheduling problem involved sequence dependent setup times in discrete stages; parallel batch processors with incompatible and compatible job families at the first and last stages of the HFS, respectively. The computational results show that the model can provide good solutions in a reasonable CPU times for the HFS under study.