A novel and efficient mathematical optimization model for multi-stage assembly flow shop considering post-processing

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Author(s):	da Silva Santana, Jose Renatho ; Fuchigami, Helio Yochihiro Total Authors: 2
Document type:	Journal article
Source:	JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING; v. N/A, p. 13-pg., 2024-06-29.
Abstract
We addressed the multistage assembly flow shop problem with post-processing and makespan minimization, a production environment commonly encountered in diverse industries such as automotive, dental, medical equipment, and clothing manufacturing. In this context, we presented an innovative mixed-integer linear programming model with a position-based strategy. Our proposed formulation demonstrated remarkable efficiency when compared to the model of the literature. It achieved optimal solutions in 77.16% of instances, with an average optimality gap of 10.59%. This study constitutes a significant contribution to the efficient resolution of a practical and frequently encountered scheduling problem that has received relatively limited attention in existing literature. The findings highlight the crucial role of mathematical optimization models as valuable decision-making tools for scheduling within the addressed production system. [GRAPHICS] (AU)

FAPESP's process:	22/05803-3 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings
Grantee:	Reinaldo Morabito Neto
Support Opportunities:	Research Projects - Thematic Grants