Export file:


  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text


  • Citation Only
  • Citation and Abstract

An integrated approach for remanufacturing job shop scheduling with routing alternatives

1 College of Engineering and Technology, Southwest University, Chongqing, 400715, China
2 State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China
3 Department of Electrical and Computer Engineering, Rowan University, Glassboro, NJ 08028, USA

Special Issues: Optimization methods in Intelligent Manufacturing

Remanufacturing is a practice of growing importance due to increasing environmental awareness and regulations. However, the stochastic natures inherent in the remanufacturing processes complicate its scheduling. This paper undertakes the challenge and presents a remanufacturing job shop scheduling approach by integrating alternative routing assignment and machine resource dispatching. A colored timed Petri net is introduced to model the dynamics of remanufacturing process, such as various process routings, uncertain operation times for cores, and machine resource conflicts. With the color attributes in Petri nets, two types of decision points, recovery routing selection and resource dispatching, are introduced and linked with places in CTPN model. With time attributes in Petri nets, the temporal aspect of recovery operations for cores as well as the evolution dynamics in cores’ operational stages is mathematically analyzed. A hybrid meta-heuristic algorithm embedded scheduling strategy over CTPN is proposed to search for the optimal recovery routings for worn cores and their recovery operation sequences on workstations, in minimizing the total production cost. The approach is demonstrated through the remanufacturing of used machine tool and its effectiveness is compared against another two cases: baseline case with fixed recovery process routings and case 2 using standard SA/MST.
  Article Metrics

Keywords remanufacturing; job shop; scheduling; colored timed petri nets; simulated annealing

Citation: Lingling Li, Congbo Li, Li Li, Ying Tang, Qingshan Yang. An integrated approach for remanufacturing job shop scheduling with routing alternatives. Mathematical Biosciences and Engineering, 2019, 16(4): 2063-2085. doi: 10.3934/mbe.2019101


  • 1. G. D. Li, M. Reimann and W. H. Zhang, When remanufacturing meets product quality improvement: The impact of production cost, Eur. J. Oper. Res., 271 (2018), 913–925.
  • 2. P. V. Loon and L. N. V. Wassenhove, Assessing the economic and environmental impact of remanufacturing: a decision support tool for OEM suppliers, Int. J. Prod. Res., 56 (2017), 1662–1674.
  • 3. M. Matsumoto, K. Chinen and H. Endo, Remanufactured auto parts market in Japan: Historical review and factors affecting green purchasing behavior, J. Clean Prod., 172 (2018), 4494–4505.
  • 4. B. M. Liu, D. J. Chen and W. J. Zhou, The effect of remanufacturing and direct reuse on resource productivity of China's automotive production, J. Clean Prod., 194 (2018), 309–317.
  • 5. Y. F. Zhang, S. C. Liu and Y. Liu, The 'Internet of Things' enabled real-time scheduling for remanufacturing of automobile engines, J. Clean Prod., 185 (2018), 562–575.
  • 6. J. Zhou and Q. W. Deng, An environmental benefits and costs assessment model for remanufacturing process under quality uncertainty, J. Clean Prod., 186 (2018), 180–190.
  • 7. R. Kumar and P. Ramachandran, Revenue management in remanufacturing: perspectives, review of current literature and research directions, Int. J. Prod. Res., 54 (2016), 2185–2201.
  • 8. V. D. R. Guide, R. Srivastava and M. E. Kraus, Priority scheduling policies for repair shops, Int. J. Prod. Res., 38 (2000), 929–950.
  • 9. V. D. R. Guide, G. C. Souza and E. V. D. Lann, Performance of static priority rules for shared facilities in a remanufacturing shop with disassembly and reassembly, Eur. J. Oper. Res., 164 (2005), 341–353.
  • 10. R. H. Teunter, K. Kaparis and O. Tang, Multi-product economic lot scheduling problem with separate production lines for manufacturing and remanufacturing, Eur. J. Oper. Res., 191 (2008), 1241–1253.
  • 11. S. Zanoni, A. Segerstedt, O. Tang, et al., Multi-product economic lot scheduling problem with manufacturing and remanufacturing using a basic period policy, Comput. Ind. Eng., 62 (2012), 1025–1033.
  • 12. H. Sun, W. D. Chen, B. Y. Liu, et al., Economic lot scheduling problem in a remanufacturing system with returns at different quality grades, J. Clean Prod., 170 (2018), 559–569.
  • 13. M. G. Kim, J. M. Yu and D. H. Lee, Solution algorithms for scheduling flow-shop-type remanufacturing systems. The 14th Asia Pacific Industrial Engineering and Management System Conference Vietnam, December 8–11, (2013).
  • 14. P. B. Luh, D. Q. Yu, S. Soorapanth, et al., Relaxation based approach to schedule asset overhaul and repair services, IEEE T. Autom. Sci. Eng., 2 (2005), 145–157.
  • 15. H. J. Wen, S. W. Hou, Z. H. Liu, et al., Integrated lot sizing and energy-efficient job shop scheduling problem in manufacturing/remanufacturing systems, Chaos Solitons Fractals, 105 (2017), 69–76.
  • 16. R. Zhang, S. K. Ong and A. Y. C. Nee, A simulation-based genetic algorithm approach for remanufacturing process planning and scheduling, Appl. Soft. Comput., 37 (2016), 521–532.
  • 17. C. B. Li, Y. Tang, C. C. Li, et al., A modeling approach to analyze variability of remanufacturing process routing, IEEE T. Autom. Sci. Eng., 10 (2013), 86–89.
  • 18. S. E. Zhao, Y. L. Li and R. Fu, Fuzzy reasoning Petri nets and its application to disassembly sequence decision-making for the end-of-life product recycling and remanufacturing, Int. J. Comput. Integr. Manuf., 27 (2014), 415–421.
  • 19. Y. Tang, M. C. Zhou and M. M Gao, Fuzzy-Petri-net-based disassembly planning considering human factors, IEEE T. Syst. Man Cybern. Syst., 36 (2006), 718–726.
  • 20. L. L. Li, C. B. Li and Y. Tang, An integrated approach of reverse engineering aided remanufacturing process for worn components, Robot. Comput. Integr. Manuf., 48 (2017), 39–50.
  • 21. D. H. Wu and W. Zheng, Formal model-based quantitative safety analysis using timed Coloured Petri Nets, Reliab. Eng. Syst. Saf., 176 (2018), 62–79.
  • 22. H. L. Liao, Q. W. Deng and Y. R. Wang, An environmental benefits and costs assessment model for remanufacturing process under quality uncertainty, J. Clean Prod., 178 (2018), 45–58.
  • 23. G. D. Li, M. Reimann and W. H. Zhang, When remanufacturing meets product quality improvement: The impact of production cost, Eur. J. Oper. Res., 271 (2018), 913–925.
  • 24. J. Y. Sheng and D. Prescott, A hierarchical coloured Petri net model of fleet maintenance with cannibalisation, Reliab. Eng. Syst. Saf., 168 (2017), 290–305.
  • 25. S. A. Hussain, N. A. Khan and A. Sadiq, Simulation, modeling and analysis of master node election algorithm based on signal strength for VANETs through Colored Petri nets, Neural Comput. Appl., 29 (2018), 1243–1259.
  • 26. Y. W. Si, V. I. Chan, M. Dumas, et al., A Petri nets based generic genetic algorithm framework for resource optimization in business processes, Simul. Model. Pract. Theory, 86 (2018), 72–101.
  • 27. A. Assad and K. Deep, A Hybrid Harmony search and Simulated Annealing algorithm for continuous optimization, Inf. Sci., 450 (2018), 246–266.
  • 28. Z. Y. Liu, Z. S. Liu, Z. P. Zhu, et al., Simulated annealing for a multi-level nurse rostering problem in hemodialysis service, Appl. Soft. Comput., 64 (2017), 148–160.
  • 29. F. Erchiqui, Application of genetic and simulated annealing algorithms for optimization of infrared heating stage in thermoforming process, Appl. Therm. Eng., 128 (2018), 1273–1272.
  • 30. X. Y. Li, C. Lu, L. Gao, et al., An effective multi-objective algorithm for energy efficient scheduling in a real-life welding shop, IEEE T. Ind. Inform., 14 (2018), 5400–5409.
  • 31. S. Hore, A. Chatterjee and A. Dewanji, Improving variable neighborhood search to solve the traveling salesman problem, Appl. Soft. Comput., 68 (2018), 83–91.
  • 32. X. Y. Li, L. Gao, Q. K. Pan, et al., An effective hybrid genetic algorithm and variable neighborhood search for integrated process planning and scheduling in a packaging machine workshop, IEEE T. Syst. Man. Cybern. Syst., (2018).
  • 33. Y. Z. Zhou, W. C. Yi, L. Gao, et al., Adaptive differential evolution with sorting crossover rate for continuous optimization problems, IEEE T. Cybern., 47 (2017), 2742–2753.
  • 34. X. Y. Li and L. Gao, An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem. Int. J. Prod. Econ., 174 (2016), 93–110.
  • 35. G. R. Amin and A. El-Bouri, A minimax linear programming model for dispatching rule selection, Comput. Ind. Eng., 121 (2018), 27–35.
  • 36. P. Neammanee and M. Reodecha, A memetic algorithm-based heuristic for a scheduling problem in printed circuit board assembly, Comput. Ind. Eng., 56 (2009), 294–305.
  • 37. B. N. Silva, M. Khan and K. Han, Load balancing integrated least slack time-based appliance scheduling for smart home energy management, Sensors, 18 (2018).


This article has been cited by

  • 1. Shuo Zhu, Hua Zhang, Zhigang Jiang, Bernard Hon, A carbon efficiency upgrading method for mechanical machining based on scheduling optimization strategy, Frontiers of Mechanical Engineering, 2020, 10.1007/s11465-019-0572-8

Reader Comments

your name: *   your email: *  

© 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved