Hybrid heuristic for the production replanning problem under varying demands in manufacturing industries

Abstract

This study aims to solve a one-dimensional multi-period cutting stock production replanning problem encountered in manufacturing industry cutting departments, considering pattern-setup costs. For operational purposes, long-term coordinated production and cutting plans are often created based on predicted demand. However, real demand may differ from predictions, and replanning may be warranted by changing conditions. A mixed-integer mathematical model was proposed by minimizing both the production cost and the cost of deviating from established plans. In addition, a hybrid dynamic programming-based heuristic was proposed. Extensive experiments were conducted on randomly generated instances. The influences on the solutions are analysed by varying the holding cost per unit and the deviation cost. Finally, the proposed heuristic is applied to enterprise practice, and the results indicate that the total cost can be expected to be reduced by 14.55% on average.

Keywords:

• Cutting stock problem
• production replanning
• hybrid heuristic
• dynamic programming

Data availability statement

The data that support the findings of this study are openly available in [OSF.io] at https://osf.io/kve53.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors would like to acknowledge financial support from the National Natural Science Foundation of China (NSFC) [Grant Nos 72101200, 71901037 and 71573204]; the China Postdoctoral Science Foundation [Grant No. 2020M38651]; and the National Natural Science Foundation of Shaanxi Province [Grant No. 2020JQ-395].