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

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.

GRAPHICAL ABSTRACT

KEYWORDS:

• Scheduling
• assembly flow shop
• mixed-integer linear programming
• mathematical optimization
• multi-stage shop
• post-processing

Acknowledgments

The authors are grateful to Sao Paulo Research Foundation (FAPESP) for the financial support (grant number 2022/05803-3) and the research productivity scholarship (PPGEP-FCT/UFG 03/2022).

Disclosure statement

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

Availability of data and materials

The data sets, results of all computational tests, statistical analyses, and source code are available upon request.

Additional information

Funding

The work was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo [2022/05803-3].

Notes on contributors

Jose Renatho da Silva Santana

José Renatho da Silva Santana is a Production Engineer from the Pontifical Catholic University of Goiás. Master in Production Engineering from Federal University of Goias (UFG). He works as a researcher in the field of Production Scheduling. He has knowledge in project management with a focus on Agile Methodologies. He currently works as a project manager in a consulting and advisory company for companies with e-commerce. Developed research and extension projects in the food industry with a focus on reducing costs and waste, as well as having experience in developing projects focused on Lean Manufacturing and people management in the application of agile routines focused on strategic and operational results in companies of different segments.

Helio Yochihiro Fuchigami

Helio Yochihiro Fuchigami is a Professor and researcher at the Federal University of São Carlos (UFSCar). He researches in the Production Scheduling and Operational Research area. Computer Scientist from UNESP, Master and PhD in Production Engineering from USP, with part of his doctorate at the Polytechnic University of Valencia, Spain. Post-doctorate at the University of New South Wales (Australian Defense Force Academy) in Australia and at UNESP/São José do Rio Preto.