Differential evolution method for stochastic flow shop scheduling with limited buffers

The flow shop scheduling problem (FSSP) with limited buffers constraint is a typical NP-hard combinatorial optimization problem and represents an important area in production scheduling. In this paper, a class of differential evolution (DE) method with the optimal computing budget allocation (OCBA) technique and hypothesis test (HT), namely OHTDE, is proposed for the stochastic flow shop scheduling with limited buffers between consecutive machines to minimize the maximum completion time (i.e., makespan). In the OHTDE, the population-based search mechanism of DE and a special crossover are applied for well exploration and exploitation, and the OCBA technique is used to allocate limited sampling budgets to provide reliable evaluation and identification for good individuals. Meanwhile, HT is also applied to perform a statistical comparison to avoid some repeated search to some extent. The results and comparisons demonstrate the superiority of OHTDE in terms of effectiveness and robustness.