JOINT OPTIMIZATION OF CAPACITATED LOT-SIZING WITH LOST SALES AND NON-CYCLICAL PREVENTIVE MAINTENANCE

Authors

  • Yuhan Guo School of Science, Zhejiang University of Science and Technology, Hangzhou, China
  • Mustapha Hrouga Department of Finance, Operations, and Marketing, Brest Business School, 29200 Brest, France
  • Jiayao Liu School of Software, Liaoning Technical University, Fuxin, China
  • Sohaib Afifi Laboratoire de Génie Informatique et d’Automatique de l’Artois (LGI2A), Univ. Artois, UR 3926, F-62400 Béthune, France
  • Hamid Allaoui Laboratoire de Génie Informatique et d’Automatique de l’Artois (LGI2A), Univ. Artois, UR 3926, F-62400 Béthune, France
  • Yu Zhang School of Economics and Management, Beihang University, Beijing, China

DOI:

https://doi.org/10.23055/ijietap.2022.29.3.8013

Abstract

Joint optimization of maintenance and lot-sizing-related operations offers significant benefits for businesses. This research studies the joint optimization of non-cyclical preventive maintenance and capacitated lot-sizing with lost sales. The objective is to determine the optimal lot size in each period, decide the optimal preventive maintenance for servicing machines over a planning horizon, and minimize the total cost related to service, operation, setup, production, inventory, and lost sales. An innovative framework is proposed to solve the problem, consisting of a novel mixed-integer linear programming formulation and an approximative production-planning algorithm combined with a multi-neighborhood descendent approach. Extensive experiments based on real-world data are conducted to verify the effectiveness of the proposed framework.

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Published

2022-06-14

How to Cite

Guo, Y., Hrouga, M., Liu, J., Afifi, S., Allaoui, H., & Zhang, Y. (2022). JOINT OPTIMIZATION OF CAPACITATED LOT-SIZING WITH LOST SALES AND NON-CYCLICAL PREVENTIVE MAINTENANCE. International Journal of Industrial Engineering: Theory, Applications and Practice, 29(3). https://doi.org/10.23055/ijietap.2022.29.3.8013

Issue

Vol. 29 No. 3 (2022)

Section

Production Planning and Control

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