Application Research for Multiobjective Low-Carbon Flexible Job-Shop Scheduling Problem Based on Hybrid Artificial Bee Colony Algorithm

This paper proposes a hybrid artificial bee colony (HABC) to solve the multiobjective low-carbon flexible job-shop scheduling problem (MLFJSP). HABC algorithm uses two-layer coding method establish initial population as nectar source for employed bees. In optimization process, phase and onlooker adopt improved crossover mutation strategies adaptive neighborhood search generate new sources, greedy is used retain better solutions. The scout update mechanism prevents from falling into local optimum enhances convergence of algorithm. order prevent loss optimal solution, results each are saved in Pareto archive (PA). Finally, two sets international standard instances carry out simulation experiments. After analyzing results, it concluded that an effective job shop problem.