多目标柔性作业车间低碳调度研究
Research on low carbon scheduling of multi-objective flexible job shop
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摘要: 针对作业车间低碳调度问题，提出了基于遗传变邻域混合算法的多目标柔性作业车间低碳调度模型.该模型在核算机械加工系统碳排放量时，综合考虑了由机器消耗能源直接产生的碳排放和处理废弃物间接产生的碳排放，建立了完工时间、机器总负载和碳排放量的目标函数，并采用多目标加权法对目标函数进行加权求和，最后利用遗传变邻域混合算法对调度模型进行求解.仿真结果表明，本文模型可以在保证完工时间和设备利用率均衡的前提下，减少生产过程中的碳排放量，验证了该模型的可行性和有效性.Abstract: Aiming at the low carbon job shop scheduling problem, a low carbon scheduling model of multi-objective flexible job shop based on genetic variable neighborhood hybrid algorithm was proposed. When calculating the carbon emissions of mechanical processing system, the carbon emissions directly generated by machine energy consumption and indirect carbon emissions from waste treatment were comprehensively considered. The objective functions of completion time, total machine load and carbon emissions were established. The multi-objective weighting method was used to sum up the objective functions. Finally, the genetic variable neighborhood hybrid algorithm was used to optimize the scheduling model. The simulation results showed that the model could reduce carbon emissions in the production process under the premise of ensuring the balance of completion time and equipment utilization, which verified the feasibility and effectiveness of the model.
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