IDEAS home Printed from https://ideas.repec.org/r/inm/oropre/v8y1960i2p219-223.html
   My bibliography  Save this item

On the Job-Shop Scheduling Problem

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Da Col, Giacomo & Teppan, Erich C., 2022. "Industrial-size job shop scheduling with constraint programming," Operations Research Perspectives, Elsevier, vol. 9(C).
  2. Blazewicz, Jacek & Domschke, Wolfgang & Pesch, Erwin, 1996. "The job shop scheduling problem: Conventional and new solution techniques," European Journal of Operational Research, Elsevier, vol. 93(1), pages 1-33, August.
  3. Juan Pablo Vielma, 2018. "Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139," Management Science, INFORMS, vol. 64(10), pages 4721-4734, October.
  4. Abdennour Azerine & Mourad Boudhar & Djamal Rebaine, 2022. "A two-machine no-wait flow shop problem with two competing agents," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 168-199, January.
  5. Biskup, Dirk & Feldmann, Martin, 2005. "On scheduling around large restrictive common due windows," European Journal of Operational Research, Elsevier, vol. 162(3), pages 740-761, May.
  6. 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.
  7. Chong Peng & Guanglin Wu & T Warren Liao & Hedong Wang, 2019. "Research on multi-agent genetic algorithm based on tabu search for the job shop scheduling problem," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-19, September.
  8. Russell, Arya & Taghipour, Sharareh, 2019. "Multi-objective optimization of complex scheduling problems in low-volume low-variety production systems," International Journal of Production Economics, Elsevier, vol. 208(C), pages 1-16.
  9. Stefan Bock, 2016. "Finding optimal tour schedules on transportation paths under extended time window constraints," Journal of Scheduling, Springer, vol. 19(5), pages 527-546, October.
  10. Jonas Harbering & Abhiram Ranade & Marie Schmidt & Oliver Sinnen, 2019. "Complexity, bounds and dynamic programming algorithms for single track train scheduling," Annals of Operations Research, Springer, vol. 273(1), pages 479-500, February.
  11. Liangliang Jin & Qiuhua Tang & Chaoyong Zhang & Xinyu Shao & Guangdong Tian, 2016. "More MILP models for integrated process planning and scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4387-4402, July.
  12. Bahman Naderi & Rubén Ruiz & Vahid Roshanaei, 2023. "Mixed-Integer Programming vs. Constraint Programming for Shop Scheduling Problems: New Results and Outlook," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 817-843, July.
  13. Gupta, Jatinder N.D. & Stafford, Edward Jr., 2006. "Flowshop scheduling research after five decades," European Journal of Operational Research, Elsevier, vol. 169(3), pages 699-711, March.
  14. Jian Zhang & Guofu Ding & Yisheng Zou & Shengfeng Qin & Jianlin Fu, 2019. "Review of job shop scheduling research and its new perspectives under Industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1809-1830, April.
  15. Ullrich, Christian A., 2013. "Integrated machine scheduling and vehicle routing with time windows," European Journal of Operational Research, Elsevier, vol. 227(1), pages 152-165.
  16. Stéphane Dauzère-Pérès & Sigrid Lise Nonås, 2023. "An improved decision support model for scheduling production in an engineer-to-order manufacturer," 4OR, Springer, vol. 21(2), pages 247-300, June.
  17. Bahman Naderi & Vahid Roshanaei & Mehmet A. Begen & Dionne M. Aleman & David R. Urbach, 2021. "Increased Surgical Capacity without Additional Resources: Generalized Operating Room Planning and Scheduling," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2608-2635, August.
  18. Tseng, Fan T. & Stafford, Edward F. & Gupta, Jatinder N. D., 2004. "An empirical analysis of integer programming formulations for the permutation flowshop," Omega, Elsevier, vol. 32(4), pages 285-293, August.
  19. Shishvan, Masoud Soleymani & Benndorf, Jörg, 2019. "Simulation-based optimization approach for material dispatching in continuous mining systems," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1108-1125.
  20. Bertsimas, Dimitris & Gupta, Shubham & Lulli, Guglielmo, 2014. "Dynamic resource allocation: A flexible and tractable modeling framework," European Journal of Operational Research, Elsevier, vol. 236(1), pages 14-26.
  21. Edzard Weber & Anselm Tiefenbacher & Norbert Gronau, 2019. "Need for Standardization and Systematization of Test Data for Job-Shop Scheduling," Data, MDPI, vol. 4(1), pages 1-21, February.
  22. Julia Lange & Frank Werner, 2018. "Approaches to modeling train scheduling problems as job-shop problems with blocking constraints," Journal of Scheduling, Springer, vol. 21(2), pages 191-207, April.
  23. Park, Myoung-Ju & Ham, Andy, 2022. "Energy-aware flexible job shop scheduling under time-of-use pricing," International Journal of Production Economics, Elsevier, vol. 248(C).
  24. Ming Zhang & Yang Lu & Youxi Hu & Nasser Amaitik & Yuchun Xu, 2022. "Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization," Sustainability, MDPI, vol. 14(9), pages 1-16, April.
  25. Xinyu Yao & Karmel S. Shehadeh & Rema Padman, 2024. "Multi-resource allocation and care sequence assignment in patient management: a stochastic programming approach," Health Care Management Science, Springer, vol. 27(3), pages 352-369, September.
  26. Madiha Harrabi & Olfa Belkahla Driss & Khaled Ghedira, 2021. "A hybrid evolutionary approach to job-shop scheduling with generic time lags," Journal of Scheduling, Springer, vol. 24(3), pages 329-346, June.
  27. Bentao Su & Naiming Xie, 2020. "Single workgroup scheduling problem with variable processing personnel," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(2), pages 671-684, June.
  28. Taejong Joo & Hyunyoung Jun & Dongmin Shin, 2022. "Task Allocation in Human–Machine Manufacturing Systems Using Deep Reinforcement Learning," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
  29. Sandy Spiers & Hoa T. Bui & Ryan Loxton & Moussa Reda Mansour & Kylie Hollins & Richard Francis & Christopher Martindale & Yogesh Pimpale, 2024. "Bayer digestion maintenance optimisation with lazy constraints and Benders decomposition," Annals of Operations Research, Springer, vol. 338(1), pages 269-302, July.
  30. Masmoudi, Oussama & Delorme, Xavier & Gianessi, Paolo, 2019. "Job-shop scheduling problem with energy consideration," International Journal of Production Economics, Elsevier, vol. 216(C), pages 12-22.
  31. Roshanaei, Vahid & Naderi, Bahman, 2021. "Solving integrated operating room planning and scheduling: Logic-based Benders decomposition versus Branch-Price-and-Cut," European Journal of Operational Research, Elsevier, vol. 293(1), pages 65-78.
  32. JC-H Pan & J-S Chen, 2003. "Minimizing makespan in re-entrant permutation flow-shops," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 642-653, June.
  33. João Luiz Marques Andrade & Gustavo Campos Menezes, 2023. "A column generation-based heuristic to solve the integrated planning, scheduling, yard allocation and berth allocation problem in bulk ports," Journal of Heuristics, Springer, vol. 29(1), pages 39-76, February.
  34. Naderi, B. & Zandieh, M., 2014. "Modeling and scheduling no-wait open shop problems," International Journal of Production Economics, Elsevier, vol. 158(C), pages 256-266.
  35. F T Tseng & E F Stafford, 2008. "New MILP models for the permutation flowshop problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1373-1386, October.
  36. Pongcharoen, P. & Hicks, C. & Braiden, P. M. & Stewardson, D. J., 2002. "Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products," International Journal of Production Economics, Elsevier, vol. 78(3), pages 311-322, August.
  37. Pongcharoen, P. & Hicks, C. & Braiden, P. M., 2004. "The development of genetic algorithms for the finite capacity scheduling of complex products, with multiple levels of product structure," European Journal of Operational Research, Elsevier, vol. 152(1), pages 215-225, January.
  38. Bock, Stefan, 2015. "Solving the traveling repairman problem on a line with general processing times and deadlines," European Journal of Operational Research, Elsevier, vol. 244(3), pages 690-703.
  39. E F Stafford & F T Tseng & J N D Gupta, 2005. "Comparative evaluation of MILP flowshop models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(1), pages 88-101, January.
  40. Menezes, Gustavo Campos & Mateus, Geraldo Robson & Ravetti, Martín Gómez, 2017. "A branch and price algorithm to solve the integrated production planning and scheduling in bulk ports," European Journal of Operational Research, Elsevier, vol. 258(3), pages 926-937.
  41. Dominik Kramer, 2009. "Zur optimalen Abfolge von Investitionsprojekten," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 20(1), pages 89-103, May.
  42. Kan Fang & Nelson Uhan & Fu Zhao & John Sutherland, 2013. "Flow shop scheduling with peak power consumption constraints," Annals of Operations Research, Springer, vol. 206(1), pages 115-145, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.