Supply chain-oriented permutation flowshop scheduling considering flexible assembly and setup times

Abstract

Given the significant proportion of the outsourced parts, components, and the complex assembly structure of the automobiles, agriculture machinery and heavy industry equipment, distributed production and flexible assembly are much-needed production scheduling settings to optimise their global supply chains. This research extends the distributed assembly permutation flowshop scheduling problem to account for flexible assembly and sequence-independent setup times (DPFSP_FAST) in a supply chain-like setting. For this purpose, an original mixed-integer linear programming (MILP) formulation to the DPFSP_FAST problem is first investigated. Considering makespan as the optimisation criterion, constructive heuristic and customised metaheuristic algorithms are then proposed to solve this emerging scheduling extension. Through extensive computational experiments, it is shown that the proposed algorithms outperform the existing best-performing algorithms to solve the DPFSP_FAST problem, yielding the best-found solutions in nearly all of the benchmark instances. Narrowing the gap between theory and practice, this study helps integrate the production planning scheduling across the supply chain.

KEYWORDS:

• Scheduling
• distributed manufacturing
• permutation flowshop
• flexible assembly
• metaheuristics

Disclosure statement

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

Additional information

Funding

This research was partially supported by the Ministry of Science and Technology, Taiwan, under Grant.MOST [109-2221-E-027-073].

Notes on contributors

Kuo-Ching Ying

Kuo-Ching Ying is currently a Distinguished Professor of the Department of Industrial Engineering and Management at the National Taipei University of Technology. He is the (senior) Editor of ten international journals. His research interests focus on the operations scheduling and combinatorial optimisation, in which he has published over 100 academic research papers in refereed international journals, such as Applied Intelligence, Applied Soft Computing, Computers and Operations Research, Computers and Industrial Engineering, European Journal of Industrial Engineering, European Journal of Operational Research, IEEE Access, International Journal of Production Economics, International Journal of Advanced Manufacturing Technology, International Journal of Innovational Computing, Information and Control, International Journal of Production Research, Journal of the Operational Research Society, OMEGA–The International Journal of Management Sciences, Production Planning & Control, Transportation Research Part E: Logistics and Transport Review, among others.

Pourya Pourhejazy

Pourya Pourhejazy received the master’s degree in industrial engineering from University Technology Malaysia, in 2014, and the Ph.D. degree in logistics engineering from INHA University, South Korea, in 2017. He is currently a Research Assistant Professor in Industrial Engineering and an Adjunct Assistant Professor in Management with the National Taipei University of Technology, Taiwan. His research interests include optimisation and decision analysis in the supply chain, production, and transportation contexts.

Chen-Yang Cheng

Chen-Yang Cheng received his Ph.D. in Industrial and Manufacturing Engineering at Penn State University. He is currently a Professor in the Department of Industrial Engineering and Management at National Taipei University of Technology. His research interests include Computer Integrated Manufacturing, Human-Computer Interaction, Distributed Systems and Control, Intelligent Systems.

Ren-Siou Syu

Ren-Siou Syu currently works as an IE Engineer at Powertech Technology Inc. He received his Master degree from Industrial Engineering and Management in National Taipei University of Technology, Taiwan. His research interests focus on the operations research and production scheduling.