基于机床加工匹配特性的混合流水车间绿色生产调度

Sustainable scheduling for hybrid flow-shop based on performance matching of machine tools

针对混合流水车间绿色生产过程中的设备选择和调度目标匹配问题,提出基于机床加工特性的多目标调度模型和改进遗传算法。该算法建立了混合流水车间调度的时间、能耗与成本优化模型,采用模糊隶属方法描述了机床加工特性,在遗传算法求解过程中通过机床加工特性隶属度与调度目标的权重系数匹配关系,建立了自适应的交叉、变异和优势保留策略,在每一代迭代中提高在调度目标方向上的选择压力,加速收敛。通过实例分析对比了不同算法的优化结果,从而验证了模型及算法的有效性,并提出了高效、节能、经济和综合4种调度生产模式,为混合流水车间绿色生产提供了指导。

To solve the problem of hybrid flow-shop sustainable scheduling, a multi-objective optimization model and modified genetic algorithm were proposed based on the performance of machine tools. The production time, energy consumption and cost in hybrid flow-shop were elaborated in the proposed mathematical model, and the performance of the machine tools in hybrid-shop were described with fuzzy membership method. In the modified GA algorithm, the adaptive crossover, mutation and elitist strategy were established according to the relationship between the membership degree of machine tools and weights of optimization objectives. Thus the selection pressure to the proper direction could be obtained so as to accelerate the convergence speed in the iteration of GA. A case study was used to verify the established model and algorithm by comparing the results obtained by different GA methods. Based on the optimization results, four kinds of typical workshop production scheduling modes including high efficiency, energy conservation, economy and comprehensive production were put forward to provide guidance for the sustainable production of hybrid flow-shop scheduling.