Group scheduling in hybrid flexible flowshop with sequence-dependent setup times and random breakdowns via integrating genetic algorithm and simulation

In this paper, the problem of group scheduling in hybrid flexible flowshop with sequence-dependent setup times is studied. Owning to its algorithmic complexity and since the problem belongs to NP-hard class, utilisation of meta-heuristic algorithms is justified to tackle the potential complexity of the problem considered. Moreover, to further actualise the problem, one of the practical, yet rarely used assumptions is incorporated in this study: 'stochastic breakdowns'. By releasing this assumption and thanks to dynamic nature of the problem, the structural complexity increases markedly. In this regard, to overcome this form of complexity, simulation techniques are typically employed. Eventually, since the problem possesses both types of complexities (algorithm complexity and structural complexity), simulation is integrated with one of the most widely-used meta-heuristic approaches, namely genetic algorithm, to minimise the expected average of completion times. What is more, in order to analyse the impact of both the problem characteristics and the algorithmic parameters, a set of varied test samples are generated. Consequently, the obtained results are explored using Taguchi experimental design method.