Genetic Algorithm-Based Batch Filling Scheduling in the Steel Industry

Abstract

Štore Steel Ltd. faces the problem of producing a huge amount (approximately 1400) of different steel compositions in relatively small quantities (approximately 15 tons). This production is performed in batches of predetermined quantities (50–53 tons). The purpose of this article is to present the methodology for optimizing the production of predetermined steel grades in predetermined quantities before a customer's set deadline in such a way as to reduce the non-planned and ordered quantities with the date ahead of the deadline and to minimize the number of batches. The genetic algorithm method was used for optimization. The results of the genetic algorithm–based batch filling scheduling have been used in practice since 2006. The non-planned and ordered steel quantities with the date ahead of the deadline have been reduced from 17.17% to 10.12% since then.

Keywords:

• Continuous casting
• Genetic algorithm
• Optimization
• Scheduling
• Steel grade
• Steelmaking
• Work orders

ACKNOWLEDGMENT

The authors would like to thank Mr. Jože Vrbovšek for sharing the intellectual territory. The project was funded by Štore Steel Ltd. and the Slovenian Research Agency under grant Program Group P2-0379 Modeling of Materials and Processes.

Notes

¹Czech State Norm.

²Society of Automotive Engineers standard.