4.7 Article

A hybrid DBH-VNS for high-end equipment production scheduling with machine failures and preventive maintenance activities

出版社

ELSEVIER
DOI: 10.1016/j.cam.2020.113195

关键词

Variable neighborhood search; Black hole algorithm; Deteriorating effect; Parallel-batching scheduling; Maintenance planning

资金

  1. National Key Research and Development Program of China [2019YFB1705300]
  2. Fundamental Research Funds for the Central Universities [JZ2020HGTB0035, JZ2019HGTA0051, JZ2019HGBZ0131]
  3. National Natural Science Foundation of China [71871080, 71801071, 71922009, 71601065, 71690235, 71501058, 71601060]
  4. Innovative Research Groups of the National Natural Science Foundation of China [71521001]
  5. Anhui Province Natural Science Foundation [1908085MG223]
  6. Project of Key Research Institute of Humanities and Social Science in University of Anhui Province
  7. Open Research Fund Program of Key Laboratory of Process Optimization and Intelligent Decision-making (Hefei University of Technology)
  8. Ministry of Education
  9. Base of Introducing Talents of Discipline to Universities for Optimization and Decision-making in the Manufacturing Process of Complex Product (111 project) [B17014]
  10. Humboldt Research Award

向作者/读者索取更多资源

The paper proposes a hybrid metaheuristic method to tackle the challenges in the production process of high-end equipment, aiming to achieve automation, integration, and intelligence through maintenance planning and order scheduling optimization. The problem is proven to be NP-hard, thus the authors propose a hybrid discrete black hole algorithm and variable neighborhood search (DBH-VNS) approach to solve the problem.
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. (C) 2020 Elsevier B.V. All rights reserved.

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