计算机集成制造系统 ›› 2018, Vol. 24 ›› Issue (第12): 3050-3059.DOI: 10.13196/j.cims.2018.12.013

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面向广义能耗的柔性作业车间调度优化模型

李聪波,雷焱绯,肖溱鸽,沈欢   

  1. 重庆大学机械传动国家重点实验室
  • 出版日期:2018-12-31 发布日期:2018-12-31
  • 基金资助:
    国家重点研发计划资助项目(2017YFF0207903);国家自然科学基金资助项目(51475059)。

Flexible job shop scheduling optimization model for generalized energy

  • Online:2018-12-31 Published:2018-12-31
  • Supported by:
    Project supported by the National Key Research and Development Program,China(No.2017YFF0207903),and the National Natural Science Foundation,China(No.51475059).

摘要: 机械加工车间能耗不仅包括机床加工过程中消耗的直接电能,还包括因消耗刀具、切削液等辅助资源产生的间接能耗。柔性作业车间中加工任务的工艺路线和加工资源可选,其调度方案灵活性强,节能潜力大。为此,研究一种综合考虑直接电能和间接能耗的柔性作业车间广义能耗调度优化模型。首先分析柔性作业车间调度直接电能和间接能耗,然后建立以车间广义能耗最低和完工时间最小为优化目标的柔性作业车间调度多目标优化模型,并基于多目标模拟退火算法对模型进行求解。最后通过案例对比分析验证了所提模型的有效性。

关键词: 广义能耗, 柔性作业车间调度, 分批调度, 多工艺路线, 绿色制造

Abstract: The energy consumption of machining workshop includes not only the direct electrical energy of machine tools consumed in the machining process but also the indirect energy consumption resulting from the use of auxiliary resources such as tool,coolant.Due to the viable alternative of process routes and processing resources for processing tasks in the flexible job shop,the scheduling schemes are highly flexible and have great potential for energy saving.Therefore,a flexible job shop scheduling optimization model for generalized energy which considered the direct electrical energy and indirect energy consumption was proposed.The direct electrical energy and indirect energy of flexible job shop scheduling was analyzed and then the flexible job shop scheduling multi-objective optimization model was established to minimize generalized energy consumption and makespan.The model was solved based on Multi-objective Simulated Annealing algorithm (MOSA).Through the comparative analysis of practical cases,the validity of the proposed model was verified.

Key words: generalized energy consumption, flexible job shop scheduling, batch splitting scheduling, alternative process routes, green manufacturing

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