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All issues Volume 57 / No 3 (May-June 2023) RAIRO-Oper. Res., 57 3 (2023) 1267-1284 References
Open Access
Issue
RAIRO-Oper. Res.
Volume 57, Number 3, May-June 2023
Page(s) 1267 - 1284
DOI https://doi.org/10.1051/ro/2023045
Published online 14 June 2023
  • J.N. Gupta and S.K. Gupta, Single facility scheduling with nonlinear processing times. Comput. Ind. Eng. 14 (1988) 387–393. [CrossRef] [Google Scholar]
  • M. Ji, X. Tang, X. Zhang and T.E. Cheng, Machine scheduling with deteriorating jobs and DeJong’s learning effect. Comput. Ind. Eng. 91 (2016) 42–47. [Google Scholar]
  • Y. Gao, J. Yuan, C.T. Ng and T.C.E. Cheng, A further study on two-agent parallel-batch scheduling with release dates and deteriorating jobs to minimize the makespan. Eur. J. Oper. Res. 273 (2019) 74–81. [CrossRef] [Google Scholar]
  • L. Tang, X. Zhao, J. Liu and J.Y.T. Leung, Competitive two-agent scheduling with deteriorating jobs on a single parallel-batching machine. Eur. J. Oper. Res. 263 (2017) 401–411. [CrossRef] [Google Scholar]
  • Y. Yin, Y. Wang, T.C.E. Cheng, W. Liu and J. Li, Parallel-machine scheduling of deteriorating jobs with potential machine disruptions. Omega 69 (2017) 17–28. [CrossRef] [Google Scholar]
  • X. Zhang, S.C. Liu, W.C. Lin and C.C. Wu, Parallel-machine scheduling with linear deteriorating jobs and preventive maintenance activities under a potential machine disruption. Comput. Ind. Eng. 145 (2020) 106482. [CrossRef] [Google Scholar]
  • S. Liu, J. Pei, H. Cheng, X. Liu and P.M. Pardalos, Two-stage hybrid flow shop scheduling on parallel batching machines considering a job-dependent deteriorating effect and non-identical job sizes. Appl. Soft Comput. 84 (2019) 105701. [CrossRef] [Google Scholar]
  • J. Pei, X. Liu, W. Fan, P.M. Pardalos and S. Lu, A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers. Omega 82 (2019) 55–69. [CrossRef] [Google Scholar]
  • K. Li, J. Chen, H. Fu, Z. Jia and J. Wu, Parallel machine scheduling with position-based deterioration and learning effects in an uncertain manufacturing system. Comput. Ind. Eng. 149 (2020) 106858. [CrossRef] [Google Scholar]
  • J. Ding, L. Shen, Z. Lü and B. Peng, Parallel machine scheduling with completion-time-based criteria and sequence-dependent deterioration. Comput. Oper. Res. 103 (2019) 35–45. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Dauzère-Pérès and L. Mönch, Scheduling jobs on a single batch processing machine with incompatible job families and weighted number of tardy jobs objective. Comput. Oper. Res. 40 (2013) 1224–1233. [Google Scholar]
  • S.S. Li and R.X. Chen, Single-machine parallel-batching scheduling with family jobs to minimize weighted number of tardy jobs. Comput. Ind. Eng. 73 (2014) 5–10. [CrossRef] [Google Scholar]
  • Z. Geng and J. Yuan, Pareto optimization scheduling of family jobs on a p-batch machine to minimize makespan and maximum lateness. Theor. Comput. Sci. 570 (2015) 22–29. [CrossRef] [Google Scholar]
  • B. Cheng, J. Cai, S. Yang and X. Hu, Algorithms for scheduling incompatible job families on single batching machine with limited capacity. Comput. Ind. Eng. 75 (2014) 116–120. [CrossRef] [Google Scholar]
  • L. Sun, A.J. Yu and B. Wu, Single machine common flow allowance group scheduling with learning effect and resource allocation. Comput. Ind. Eng. 139 (2020) 106126. [CrossRef] [Google Scholar]
  • A. Kramer, M. Iori and P. Lacomme, Mathematical formulations for scheduling jobs on identical parallel machines with family setup times and total weighted completion time minimization. Eur. J. Oper. Res. 289 (2021) 825–840. [CrossRef] [Google Scholar]
  • X. Li, Y. Li and Y. Huang, Heuristics and lower bound for minimizing maximum lateness on a batch processing machine with incompatible job families. Comput. Oper. Res. 106 (2019) 91–101. [CrossRef] [MathSciNet] [Google Scholar]
  • N. Alizadeh and A.H. Kashan, Enhanced grouping league championship and optics inspired optimization algorithms for scheduling a batch processing machine with job conflicts and non-identical job sizes. Appl. soft Comput. 83 (2019) 105657. [CrossRef] [Google Scholar]
  • E. Molaee, R. Sadeghian and P. Fattahi, Minimizing maximum tardiness on a single machine with family setup times and machine disruption. Comput. Oper. Res. 129 (2021) 105231. [CrossRef] [Google Scholar]
  • L. Mönch and S. Roob, A matheuristic framework for batch machine scheduling problems with incompatible job families and regular sum objective. Appl. Soft Comput. 68 (2018) 835–846. [CrossRef] [Google Scholar]
  • V. Abu-Marrul, R. Martinelli, S. Hamacher and I. Gribkovskaia, Matheuristics for a parallel machine scheduling problem with non-anticipatory family setup times: application in the offshore oil and gas industry. Comput. Oper. Res. 128 (2021) 105162. [CrossRef] [Google Scholar]
  • C.C. Wu and W.C. Lee, Single-machine group-scheduling problems with deteriorating setup times and job-processing times. Int. J. Prod. Econ. 115 (2008) 128–133. [CrossRef] [Google Scholar]
  • W.C. Lee and Z.S. Lu, Group scheduling with deteriorating jobs to minimize the total weighted number of late jobs. Appl. Math. Comput. 218 (2012) 8750–8757. [MathSciNet] [Google Scholar]
  • Y.T. Xu, Y. Zhang and X. Huang, Single-machine ready times scheduling with group technology and proportional linear deterioration. Appl. Math. Model. 38 (2014) 384–391. [CrossRef] [MathSciNet] [Google Scholar]
  • X. Zhang, L. Liao, W. Zhang, T.C.E. Cheng, Y. Tan and M. Ji, Single-machine group scheduling with new models of position-dependent processing times. Comput. Ind. Eng. 117 (2018) 1–5. [CrossRef] [Google Scholar]
  • P.J. Lai and W.C. Lee, Single-machine scheduling with general sum-of-processing-time-based and position-based learning effects. Omega 39 (2011) 467–471. [CrossRef] [Google Scholar]
  • G. Dósa, R. Li, X. Han and Z. Tuza, Tight absolute bound for first fit decreasing bin-packing: FFD ≤ (L)11/9OPT(L) + 6/9. Theo. Comput. Sci. 510 (2013) 13–61. [CrossRef] [Google Scholar]

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