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Review of job shop scheduling research and its new perspectives under Industry 4.0

Citations

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Cited by:

  1. Vivek Warke & Satish Kumar & Arunkumar Bongale & Ketan Kotecha, 2021. "Sustainable Development of Smart Manufacturing Driven by the Digital Twin Framework: A Statistical Analysis," Sustainability, MDPI, vol. 13(18), pages 1-49, September.
  2. Dashi Nazarov & Anton Klarin, 2020. "Taxonomy of Industry 4.0 research: Mapping scholarship and industry insights," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 535-556, July.
  3. Raja Awais Liaqait & Shermeen Hamid & Salman Sagheer Warsi & Azfar Khalid, 2021. "A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
  4. Riccardo Brozzi & David Forti & Erwin Rauch & Dominik T. Matt, 2020. "The Advantages of Industry 4.0 Applications for Sustainability: Results from a Sample of Manufacturing Companies," Sustainability, MDPI, vol. 12(9), pages 1-19, May.
  5. Tao Ren & Yan Zhang & Shuenn-Ren Cheng & Chin-Chia Wu & Meng Zhang & Bo-yu Chang & Xin-yue Wang & Peng Zhao, 2020. "Effective Heuristic Algorithms Solving the Jobshop Scheduling Problem with Release Dates," Mathematics, MDPI, vol. 8(8), pages 1-25, July.
  6. Aidin Delgoshaei & Mohd Khairol Anuar Bin Mohd Ariffin & Zulkiflle B. Leman, 2022. "An Effective 4–Phased Framework for Scheduling Job-Shop Manufacturing Systems Using Weighted NSGA-II," Mathematics, MDPI, vol. 10(23), pages 1-28, December.
  7. Chia-Yen Lee & Chen-Fu Chien, 2022. "Pitfalls and protocols of data science in manufacturing practice," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1189-1207, June.
  8. Meloni, Carlo & Pranzo, Marco & Samà, Marcella, 2022. "Evaluation of VaR and CVaR for the makespan in interval valued blocking job shops," International Journal of Production Economics, Elsevier, vol. 247(C).
  9. Gregory A. Kasapidis & Dimitris C. Paraskevopoulos & Panagiotis P. Repoussis & Christos D. Tarantilis, 2021. "Flexible Job Shop Scheduling Problems with Arbitrary Precedence Graphs," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4044-4068, November.
  10. Shahed Mahmud & Ripon K. Chakrabortty & Alireza Abbasi & Michael J. Ryan, 2022. "Switching strategy-based hybrid evolutionary algorithms for job shop scheduling problems," Journal of Intelligent Manufacturing, Springer, vol. 33(7), pages 1939-1966, October.
  11. Chen, Ziyue & Huang, Lizhen, 2021. "Digital twins for information-sharing in remanufacturing supply chain: A review," Energy, Elsevier, vol. 220(C).
  12. Chen, Wenchong & Gong, Xuejian & Rahman, Humyun Fuad & Liu, Hongwei & Qi, Ershi, 2021. "Real-time order acceptance and scheduling for data-enabled permutation flow shops: Bilevel interactive optimization with nonlinear integer programming," Omega, Elsevier, vol. 105(C).
  13. Henry Ekwaro-Osire & Dennis Bode & Klaus-Dieter Thoben & Jan-Hendrik Ohlendorf, 2022. "Identification of Machine Learning Relevant Energy and Resource Manufacturing Efficiency Levers," Sustainability, MDPI, vol. 14(23), pages 1-19, November.
  14. Amirhosein Gholami & Nasim Nezamoddini & Mohammad T. Khasawneh, 2023. "Customized orders management in connected make-to-order supply chains," Operations Management Research, Springer, vol. 16(3), pages 1428-1443, September.
  15. Dalila B. M. M. Fontes & S. Mahdi Homayouni & Mauricio G. C. Resende, 2022. "Job-shop scheduling-joint consideration of production, transport, and storage/retrieval systems," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1284-1322, September.
  16. Ying Sun & Jeng-Shyang Pan & Pei Hu & Shu-Chuan Chu, 2023. "Enhanced Equilibrium Optimizer algorithm applied in job shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 34(4), pages 1639-1665, April.
  17. Cildoz, Marta & Ibarra, Amaia & Mallor, Fermin, 2020. "Coping with stress in emergency department physicians through improved patient-flow management," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
  18. Zeba, Gordana & Dabić, Marina & Čičak, Mirjana & Daim, Tugrul & Yalcin, Haydar, 2021. "Technology mining: Artificial intelligence in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
  19. Germán González Rodríguez & Jose M. Gonzalez-Cava & Juan Albino Méndez Pérez, 2020. "An intelligent decision support system for production planning based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1257-1273, June.
  20. Monaci, Marta & Agasucci, Valerio & Grani, Giorgio, 2024. "An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents," European Journal of Operational Research, Elsevier, vol. 312(3), pages 910-926.
  21. Yaliang Wang & Xinyu Fan & Chendi Ni & Kanghong Gao & Shousong Jin, 2023. "Collaborative optimization of workshop layout and scheduling," Journal of Scheduling, Springer, vol. 26(1), pages 43-59, February.
  22. Zhao Peng & Huan Zhang & Hongtao Tang & Yue Feng & Weiming Yin, 2022. "Research on flexible job-shop scheduling problem in green sustainable manufacturing based on learning effect," Journal of Intelligent Manufacturing, Springer, vol. 33(6), pages 1725-1746, August.
  23. Wai Sze Yip & Suet To & Hongting Zhou, 2022. "Current status, challenges and opportunities of sustainable ultra-precision manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 33(8), pages 2193-2205, December.
  24. Masoud Zafarzadeh & Magnus Wiktorsson & Jannicke Baalsrud Hauge, 2021. "A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective," Logistics, MDPI, vol. 5(2), pages 1-32, April.
  25. Zigao Wu & Shaohua Yu & Tiancheng Li, 2019. "A Meta-Model-Based Multi-Objective Evolutionary Approach to Robust Job Shop Scheduling," Mathematics, MDPI, vol. 7(6), pages 1-19, June.
  26. R. Micale & C. M. La Fata & M. Enea & G. La Scalia, 2021. "Regenerative scheduling problem in engineer to order manufacturing: an economic assessment," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1913-1925, October.
  27. Ji, Bin & Zhang, Dezhi & Zhang, Zheng & Yu, Samson S. & Van Woensel, Tom, 2022. "The generalized serial-lock scheduling problem on inland waterway: A novel decomposition-based solution framework and efficient heuristic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
  28. Gabriel Mauricio Zambrano-Rey & Eliana María González-Neira & Gabriel Fernando Forero-Ortiz & María José Ocampo-Monsalve & Andrea Rivera-Torres, 2024. "Minimizing the expected maximum lateness for a job shop subject to stochastic machine breakdowns," Annals of Operations Research, Springer, vol. 338(1), pages 801-833, July.
  29. Elisa Negri & Vibhor Pandhare & Laura Cattaneo & Jaskaran Singh & Marco Macchi & Jay Lee, 2021. "Field-synchronized Digital Twin framework for production scheduling with uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1207-1228, April.
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