Research on Large Scale Flexible Job Shop Scheduling

In this work, the hybrid Gray Wolf Optimization (HGWO) algorithm that specifically designed for improving the efficiency of large scale flexible job shop scheduling problem (LSFJSP) is proposed. HGWO is formed by combining Gray Wolf Optimization (GWO) algorithm with the crossover and mutation mechanisms of genetic algorithm (GA). Besides, an along-the-way search strategy, an information exchange strategy within the population, and an alpha wolf evolution strategy are proposed in HGWO, so as to increase the global and local search capabilities. The experimental results on the Brandimarte example show that the proposed HGWO makes a significant improvement in efficiency.