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A hybrid DBH-VNS for high-end equipment production scheduling with machine failures and preventive maintenance activities
Journal of Computational and Applied Mathematics ( IF 2.4 ) Pub Date : 2020-09-12 , DOI: 10.1016/j.cam.2020.113195
Shaojun Lu , Jun Pei , Xinbao Liu , Panos M. Pardalos

The high-end equipment features with high value, complicated manufacturing process, and high status, and it thus brings a huge challenge to increase reliability, quality, and productivity during the production. In order to tackle this challenge and achieve automation, integration, and intelligence this paper proposes a hybrid metaheuristic for an integrated order scheduling and maintenance planning model with position-based processing time, parallel-batching processing, and multiple manufacturers. During the production, the continuous operation of the machine increases the probability of failure, and the repair work can eliminate the failure For each order, we derive some useful lemmas and develop an optimal algorithm to schedule jobs within it. Then, given the order assignment and sequence in the manufacturers, we propose a dynamic programing algorithm to make the decision on the maintenance planning. Subsequently, the investigated problem is proved to be NP-hard, thus, we propose a hybrid discrete black hole algorithm and variable neighborhood search (DBH-VNS) approach to solve the integrated problem. Some improvements are integrated into the proposed algorithm to obtain the competitive results, which include discrete encoding-based population updating scheme, the modified neighborhoods, and the VNS-based local search. Finally, we conduct computational experiments and the results demonstrate the effectiveness and validity of the proposed hybrid metaheuristic.



中文翻译:

混合DBH-VNS,用于具有机器故障和预防性维护活动的高端设备生产计划

高端设备具有价值高,制造工艺复杂和地位高的特点,因此在提高生产过程中的可靠性,质量和生产率方面提出了巨大的挑战。为了解决这一挑战并实现自动化,集成和智能,本文提出了一种混合元启发式方法,用于基于位置的处理时间,并行批处理和多个制造商的集成订单调度和维护计划模型。在生产过程中,机器的连续运行会增加出现故障的可能性,并且维修工作可以消除故障。对于每个订单,我们都会得出一些有用的引理,并开发一种优化算法来安排其中的作业。然后,根据制造商的订单分配和顺序,我们提出了一种动态编程算法来决定维护计划。随后,被研究的问题被证明是NP难的,因此,我们提出了一种混合离散黑洞算法和可变邻域搜索(DBH-VNS)的方法来解决该综合问题。所提出的算法中集成了一些改进以获得竞争结果,包括基于离散编码的种群更新方案,修改后的邻域以及基于VNS的本地搜索。最后,我们进行了计算实验,结果证明了所提出的混合元启发式方法的有效性和有效性。我们提出了一种混合离散黑洞算法和可变邻域搜索(DBH-VNS)方法来解决集成问题。所提出的算法中集成了一些改进以获得竞争结果,包括基于离散编码的种群更新方案,修改后的邻域以及基于VNS的本地搜索。最后,我们进行了计算实验,结果证明了所提出的混合元启发式方法的有效性和有效性。我们提出了一种混合离散黑洞算法和可变邻域搜索(DBH-VNS)方法来解决集成问题。所提出的算法中集成了一些改进以获得竞争结果,包括基于离散编码的种群更新方案,修改后的邻域以及基于VNS的本地搜索。最后,我们进行了计算实验,结果证明了所提出的混合元启发式方法的有效性和有效性。

更新日期:2020-09-18
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