An enhanced branch-and-price algorithm for the integrated production and transportation scheduling problem

ABSTRACT

Industry 4.0 technologies, such as artificial intelligence, the internet of things and 3D printing are aiding the manufacturers by complementing their skilled workforce and transforming the way factories are run. This paper studies an integrated production and transportation scheduling problem in the context of the spare parts supply chain by integrating 3D printing with JIT delivery systems. This work aims to find a synchronised production and distribution schedule that minimises the weighted sum of delivery times and transportation costs. Based on the characteristics of the problem, we propose a new set-covering formulation. An enhanced branch-and-price algorithm is designed to solve the problem instances to optimality. To expedite the column generation process, two acceleration strategies are also used. The computational results are in favour of the proposed algorithm and the acceleration strategies. Further, the results indicate that integrating the production and transportation scheduling decisions leads to an average savings of about 16.27% of the total costs.

KEYWORDS:

• 3D manufacturing
• JIT delivery
• integrated production and transportation scheduling
• set-covering formulation
• branch-and-price algorithm
• acceleration strategy

Acknowledgments

We gratefully acknowledge the comments and suggestions made by the anonymous reviewers and the Editors of this journal in substantially improving the quality of this manuscript.

Disclosure statement

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

Additional information

Funding

This work was partially supported by the National Natural Science Foundation of China [grant number 71831007].

Notes on contributors

Peiyang He

Peiyang He received the B.E. degree in Mathematics and Applied Mathematics from Henan University, Henan, China, in 2016. She is currently a Ph.D. candidate in Management Science and Engineering at Huazhong University of Science and Technology, Wuhan, China. Her current research interests include combinatorial optimisation, integrated production and transportation scheduling, and supply chain management.

Kunpeng Li

Kunpeng Li received the B.E. degree in Mechanical Engineering and Automation from Huazhong University of Science and Technology, Wuhan, China, in 2001, and Ph.D. degree in Systems Engineering and Management from Nanyang Technological University, Singapore, in 2006. He is currently a Professor in School of Management, Huazhong University of Science and Technology, Wuhan, China. His current research interests include production operation management, scheduling, and supply chain management.

P. N. Ram Kumar

P. N. Ram Kumar received his B.Tech degree in Mechanical Engineering from JNTU Hyderabad in 2003, M.E. degree in Industrial Engineering from PSG College of Technology, Coimbatore in 2005 and Ph.D. from Indian Institute of Technology Madras in 2009. He is currently an Associate Professor in the QM & OM area at the Indian Institute of Management Kozhikode. His research interests are transportation network optimisation, military logistics, and routing and scheduling problems in the broad domain of operations management.