基于改进人工蜂群算法的多目标绿色柔性作业车间调度研究

针对多目标绿色柔性作业车间调度问题（MGFJSP）的特点，提出从碳排放量、噪声和废弃物这3个指标来综合评定环境污染程度，建立了以最小化最大完成时间和环境污染程度为优化目标的MGFJSP模型，并提出了一种改进的人工蜂群算法来求解该模型。算法的具体改进包括：设计了一种三维向量的编码和对应解码方案，在跟随蜂搜索阶段引入一种有效的动态邻域搜索操作来提高算法的局部搜索能力，在侦查蜂阶段提出产生新食物源的策略用于增加种群的多样性。最后进行了实验研究与算法对比，以验证所建模型和所提算法的有效性。

Research on Multi-objective Green Flexible Job-shop Scheduling Based on Improved ABC Algorithm

Aiming at the characteristics of multi-objective green flexible job-shop scheduling problem (MGFJSP), three indicators of carbon emissions, noises and wastes were proposed to evaluate the degree of environmental pollution comprehensively. A MGFJSP model was established with the optimization goals of minimizing the makespan and the degree of environmental pollution. And the improved ABC algorithm was proposed to solve this model. The specific improvements of algorithm included: a three-dimensional vector coding schemne and the corresponding decoding scheme were designed, an effective dynamic neighborhood search operation was introduced to improve the local search ability of the algorithm in the follow bee search stage, and a strategy for generating new food sources was proposed to increase the diversity of the population in the bee detection stage. Finally, the experimental study and algorithm comparison were carried out to verify the validity of the established model and the proposed algorithm.