PRODUCTION DECISION RESCHEDULING OF PREFABRICATED BUILDING PARTS SUBJECT TO INTERFERENCE FROM THE ARRIVAL OF NEW ORDERS

Authors

  • Heping Wang Anhui University of Technology
  • Hui Wang Anhui University of Technology
  • Yan Li Anhui University of Technology
  • Fuyu Wang Anhui University of Technology

DOI:

https://doi.org/10.23055/ijietap.2020.27.5.6547

Keywords:

Prefabricated building parts, improved quantum gray wolf intelligent algorithm, production rescheduling, profit-loss function

Abstract

Disruption events that occur during the production of prefabricated components present challenges for the feasibility of an original production plan. Therefore, rescheduling is of great significance in production management. In this paper, we study a rescheduling decision method for prefabricated building component production where the insertion of new orders is considered a disruption. We develop a rescheduling model for precast production to minimize the maximum completion time and design an improved grey wolf intelligent algorithm to solve the model. Furthermore, we take the initial plan as the base and establish a profit-loss function based on the saved time or the delay generated by the rescheduling plan. Finally, we conduct a case study that verifies the validity and feasibility of the rescheduling decision method and model. Our results contribute to the existing literature on rescheduling decisions by improving the stability of a production system.

Author Biographies

Heping Wang, Anhui University of Technology

School of Management Science and Engineering

Hui Wang, Anhui University of Technology

School of Management Science and Engineering

Yan Li, Anhui University of Technology

School of Management Science and Engineering

Fuyu Wang, Anhui University of Technology

School of Management Science and Engineering

Published

2021-04-29

How to Cite

Wang, H., Wang, H., Li, Y., & Wang, F. (2021). PRODUCTION DECISION RESCHEDULING OF PREFABRICATED BUILDING PARTS SUBJECT TO INTERFERENCE FROM THE ARRIVAL OF NEW ORDERS. International Journal of Industrial Engineering: Theory, Applications and Practice, 27(5). https://doi.org/10.23055/ijietap.2020.27.5.6547

Issue

Section

Special Issue on Data-driven Computational Intelligence in Industries Application