基于改进基因表达编程的柔性作业车间能效调度规则发现

Energy-efficient scheduling rules mining for flexible job shop via improved gene expression program

在全球市场竞争加剧、资源环境严管的形势下,复杂制造系统在环境排放、生产效率等方面,面临着更严格的要求。在此要求下,以柔性作业车间能效调度为研究对象,构建带开关机决策的能效调度模型,剖析问题本质,发现提高工序连续性有利于降低总能耗。为此,提出一种基于逆活动调度策略改进的基因表达编程算法,形成高效的能效调度规则。该调度规则在不延迟总完工时间的前提下,尽可能减少空闲间隔。实验结果表明,基于改进基因表达编程的调度规性能优越,设计的逆活动调度策略显著提升了能效水平。

Modern manufacturing industries have been facing on the global market completion and the environmental pressure,this prompts that flexible manufacturing system should be lower carbon and more efficient.Taking energy-efficient flexible job shop problem as the study object,an energy-efficient scheduling model with machine off-on decision making strategy was constructed.After analyzing the problem,it was found that process continuity among operations was helpful to reduce total energy consumption.To this end,an improved gene expression program with inverse activity scheduling strategy was proposed to mine new dispatching rules.This strategy tried to reduce the idle time without delaying makespan.The experimental results showed that the new dispatching rule was superior to other dispatching rules.At the same time,inverse activity scheduling strategy could enhance energy-efficient level significantly.