系统仿真学报 ›› 2024, Vol. 36 ›› Issue (6): 1344-1358.doi: 10.16182/j.issn1004731x.joss.23-0343

• 论文 • 上一篇    下一篇

考虑能耗和运输的有限缓冲区混合流水车间调度

温廷新(), 关婷誉()   

  1. 辽宁工程技术大学 工商管理学院,辽宁 葫芦岛 125105
  • 收稿日期:2023-03-27 修回日期:2023-05-16 出版日期:2024-06-28 发布日期:2024-06-19
  • 通讯作者: 关婷誉 E-mail:wen_tx@163.com;2316244404@qq.com
  • 第一作者简介:温廷新(1974-),男,教授,博士,研究方向为矿业工程、智能优化算法及应用、计算机软件及计算机应用、供应链管理等。 E-mail:wen_tx@163.com
  • 基金资助:
    国家自然科学基金(71771111);辽宁省社会科学规划基金(L14BTJ004)

Hybrid Flow Shop Scheduling with Limited Buffers Considering Energy Consumption and Transportation

Wen Tingxin(), Guan Tingyu()   

  1. School of Business Administration, Liaoning Technical University, Huludao 125105, China
  • Received:2023-03-27 Revised:2023-05-16 Online:2024-06-28 Published:2024-06-19
  • Contact: Guan Tingyu E-mail:wen_tx@163.com;2316244404@qq.com

摘要:

为解决生产调度不及时、加工过程中能耗过大等问题,构建了有限缓冲区混合流水车间调度优化模型。模型以最小化最大完工时间和车间总能耗为目标,将运输时间、广义能耗和缓冲区容量等资源限制作为约束,并应用开关机节能策略减少待机能耗,验证了优化模型的可行性;设计一种狮群算法,采用随机产生与贪婪选择相结合的种群初始化方法,提高初始解质量和求解效率,验证了狮群算法的优越性。实验结果表明:该算法能有效解决考虑能耗和运输时间的有限缓冲区混合流水车间调度问题,优化模型能依照实际需要进行柔性调节,达到制造型企业合理排产、节能减排的目的。

关键词: 混合流水车间, 综合能耗, 缓冲区, 狮群算法, 多目标优化

Abstract:

Aiming at the untimely production scheduling and excessive energy consumption during processing, a limited buffer hybrid flow shop scheduling optimization model is constructed. To minimize the makespan and total energy consumption of the workshop, the transport time, generalized energy consumption and buffer capacity being the constraints, and the on/off energy saving strategy applied to reduce the standby energy consumption, the feasibility of the optimization model are verified. A lion swarm optimization algorithm is designed, in which a population initialization method combining random generation and greedy selection is used to improve the initial solution quality and solution efficiency, the lion swarm optimization algorithm superiority is verified. The experimental results show that the algorithm can effectively solve the hybrid flow shop scheduling problem with limited buffer considering energy consumption and transportation time, and the established optimization model can be flexibly adjusted according to the actual needs, in which the purpose of rational production scheduling, energy saving and emission reduction for manufacturing enterprises can be achieved.

Key words: hybrid flow shop, comprehensive energy consumption, buffer, lion swarm optimization algorithm, multi-objective optimization

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