Parallel-batching scheduling with nonlinear processing times on a single and unrelated parallel machines (original) (raw)

References

  1. Lee, C.Y., Uzsoy, R., Martin-Vega, L.A.: Efficient algorithms for scheduling semiconductor burn-in operations. Oper. Res. Int. Journal 40, 764–775 (1992)
    MathSciNet MATH Google Scholar
  2. Malapert, A., Guéret, C., Rousseau, L.M.: A constraint programming approach for a batch processing problem with non-identical job sizes. Eur. J. Oper. Res. 3, 533–545 (2012)
    MathSciNet MATH Google Scholar
  3. Zhang, G., Cai, X., Lee, C.Y., Wong, C.K.: Minimizing makespan on a single batch processing machine with nonidentical job sizes. Nav. Res. Logist. 3, 226–240 (2001)
    MathSciNet MATH Google Scholar
  4. Dupont, L., Dhaenens-Flipo, C.: Minimizing the makespan on a batch machine with non-identical job sizes: an exact procedure. Comput. Oper. Res. 7, 807–819 (2002)
    MathSciNet MATH Google Scholar
  5. Li, C., Lee, C.Y.: Scheduling with agreeable release times and due dates on a batch processing machine. Eur. J. Oper. Res. 96, 564–569 (1997)
    MATH Google Scholar
  6. Melouk, S., Damodaran, P., Chang, P.-Y.: Minimizing makespan for single machine batch processing with nonidentical job sizes using simulated annealing. Int. J. Prod. Econ. 87, 141–147 (2004)
    Google Scholar
  7. Kumar, A., Tan, Y.: Demand effects of joint product advertising in online videos. Manage. Sci. 61, 1921–1937 (2015)
    Google Scholar
  8. Paul, A., Tan, Y., Vakharia, A.: Inventory planning for a modular product family. Prod. Oper. Manag. 24, 1033–1053 (2015)
    Google Scholar
  9. Tan, Y., Carrillo, J., Cheng, H.K.: The agency model for digital goods. Decis. Sci. 4, 628–660 (2016)
    Google Scholar
  10. Tan, Y., Carrillo, J.: Strategic analysis of the agency model for digital goods. Prod. Oper. Manag. (2017). https://doi.org/10.1111/poms.12595
    Article Google Scholar
  11. Gupta, J.N.D., Gupta, S.K.: Single facility scheduling with nonlinear processing times. Comput. Ind. Eng. 14, 387–393 (1988)
    Google Scholar
  12. Browne, S., Yechiali, U.: Scheduling deteriorating jobs on a single processor. Oper. Res. 3, 495–498 (1990)
    MATH Google Scholar
  13. Mosheiov, G.: Scheduling deteriorating jobs under simple linear deterioration. Comput. Oper. Res. 21, 653–659 (1994)
    MATH Google Scholar
  14. Cheng, T.C.E., Lee, W.C., Wu, C.C.: Single-machine scheduling with deteriorating jobs and past-sequence-dependent setup times. Appl. Math. Model. 35, 1861–1867 (2011)
    MathSciNet MATH Google Scholar
  15. Lai, P., Lee, W.C.: Single-machine scheduling with a nonlinear deterioration function. Inf. Process. Lett. 110, 455–459 (2010)
    MathSciNet MATH Google Scholar
  16. Wang, J., Wang, M.: Single-machine scheduling with nonlinear deterioration. Optimization Letters 6, 87–98 (2012)
    MathSciNet MATH Google Scholar
  17. Pei, J., Liu, X., Pardalos, P.M., Fan, W., Yang, S.: Scheduling deteriorating jobs on a single serial-batching machine with multiple job types and sequence-dependent setup times. Ann. Oper. Res. 249, 175–195 (2017)
    MathSciNet MATH Google Scholar
  18. Pei, J., Liu, X., Fan, W., Pardalos, P.M., Shaojun, L.: A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers. Omega (2017). https://doi.org/10.1016/j.omega.2017.12.003
    Article Google Scholar
  19. Fan, W., Pei, J., Liu, X., Pardalos, P.M., Kong, M.: Serial-batching group scheduling with release times and the combined effects of deterioration and truncated job-dependent learning. J. Global Optim. (2017). https://doi.org/10.1007/s10898-017-0536-7
    Article MATH Google Scholar
  20. Pei, J., Pardalos, P.M., Liu, X., Fan, W., Yang, S.: Serial batching scheduling of deteriorating jobs in a two-stage supply chain to minimize the makespan. Eur. J. Oper. Res. 244(1), 13–25 (2015)
    MathSciNet MATH Google Scholar
  21. Alidaee, B., Womer, N.K.: Scheduling with time dependent processing times: review and extensions. J. Oper. Res. Soc. 50, 711–720 (1999)
    MATH Google Scholar
  22. Cheng, T.C.E., Kang, L., Ng, C.T.: Due-date assignment and single machine scheduling with deteriorating jobs. J. Oper. Res. Soc. 55, 198–203 (2004)
    MATH Google Scholar
  23. Wu, C.C., Lee, W.C.: Scheduling linear deteriorating jobs to minimize makespan with an availability constraint on a single machine. Inf. Process. Lett. 87, 89–93 (2003)
    MathSciNet MATH Google Scholar
  24. Ji, M., He, Y., Cheng, T.C.E.: Scheduling linear deteriorating jobs with an availability constraint on a single machine. Theoret. Comput. Sci. 362, 115–126 (2006)
    MathSciNet MATH Google Scholar
  25. Wang, J.B.: Single-machine scheduling problems with the effects of learning and deterioration. Omega 35, 397–402 (2007)
    Google Scholar
  26. Cheng, T.C.E., Ding, Q., Lin, B.M.T.: A concise survey of scheduling with time-dependent processing times. Eur. J. Oper. Res. 152, 1–13 (2004)
    MathSciNet MATH Google Scholar
  27. Toksarı, M.D., Güner, E.: Minimizing the earliness/tardiness costs on parallel machine with learning effects and deteriorating jobs: a mixed nonlinear integer programming approach. Int. J. Adv. Manuf. Technol. 38, 801–808 (2008)
    Google Scholar
  28. Ji, M., Cheng, T.C.E.: Parallel-machine scheduling of simple linear deteriorating jobs. Theoret. Comput. Sci. 410, 3761–3768 (2009)
    MathSciNet MATH Google Scholar
  29. Mazdeh, M.M., Zaerpour, F., Zareei, A., Hajinezhad, A.: Parallel machines scheduling to minimize job tardiness and machine deteriorating cost with deteriorating jobs. Appl. Math. Model. 34, 1498–1510 (2010)
    MathSciNet MATH Google Scholar
  30. Li, S., Yuan, J.: Parallel-machine scheduling with deteriorating jobs and rejection. Theoret. Comput. Sci. 411, 3642–3650 (2010)
    MathSciNet MATH Google Scholar
  31. Wang, J., Wang, L., Wang, D., Wang, X.: Single-machine scheduling with a time-dependent deterioration. Int. J. Adv. Manuf. Technol. 43, 805–809 (2009)
    Google Scholar
  32. Qi, X., Zhou, S., Yuan, J.: Single machine parallel-batch scheduling with deteriorating jobs. Theoret. Comput. Sci. 410, 830–836 (2009)
    MathSciNet MATH Google Scholar
  33. Miao, C., Zhang, Y., Cao, Z.: Bounded parallel-batch scheduling on single and multi-machines for deteriorating jobs. Inf. Process. Lett. 111, 798–803 (2011)
    MathSciNet MATH Google Scholar
  34. Li, S., Ng, C.T., Cheng, T.C.E., Yuan, J.: Parallel-batch scheduling of deteriorating jobs with release dates to minimize the makespan. Eur. J. Oper. Res. 210, 482–488 (2011)
    MathSciNet MATH Google Scholar
  35. Wu, Y., Wang, M., Wang, J.: Some single-machine scheduling with both learning and deterioration effects. Appl. Math. Model. 35, 3731–3736 (2011)
    MathSciNet MATH Google Scholar
  36. Graham, R.L., Lawler, E.L., Lenstra, J.K., Rinnooy, A.H.G.: Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann. Discret. Math. 5, 287–326 (1979)
    MathSciNet MATH Google Scholar
  37. Lenstra, J.K., Rinnooy, A.H.G., Brucker, P.: Complexity of machine scheduling problems. J. Sched. 1, 343–362 (1977)
    MathSciNet MATH Google Scholar
  38. Eusuff, M.M., Lansey, K.E.: Optimization of water distribution network design using the shuffled frog leaping algorithm. J. Water Resour. Plan. Manag. 129, 210–225 (2003)
    Google Scholar
  39. Hansen, P., Mladenović, N.: Variable neighborhood search. Comput. Oper. Res. 24, 1097–1100 (1977)
    MathSciNet MATH Google Scholar
  40. Hansen, P., Mladenović, N., Pérez, J.A.M.: Variable neighbourhood search: methods and applications. 4OR 175, 367–407 (2008)
    MathSciNet MATH Google Scholar
  41. Zhou, S., Liu, M., Chen, H., Li, X.: An effective discrete differential evolution algorithm for scheduling uniform parallel batch processing machines with non-identical capacities and arbitrary job sizes. Int. J. Prod. Econ. 179, 1–11 (2016)
    Google Scholar
  42. Jiang, L., Pei, J., Liu, X., Pardalos, P.M., Yang, Y., Qian, X.: Uniform parallel batch machines scheduling considering transportation using a hybrid DPSO-GA algorithm. Int. J. Adv. Manuf. Technol. (2016). https://doi.org/10.1007/s00170-016-9156-5
    Article Google Scholar
  43. Bean, J.C.: Genetic algorithms and random keys for sequencing and optimization. ORSA J. Comput. 2, 154–160 (1994)
    MATH Google Scholar
  44. Borges, P., Eid, T., Bergseng, E.: Applying simulated annealing using different methods for the neighborhood search in forest planning problems. Eur. J. Oper. Res. 233, 700–710 (2014)
    MathSciNet MATH Google Scholar
  45. Liang, X., Li, W., Zhang, Y., Zhou, M.C.: An adaptive particle swarm optimization method based on clustering. Soft. Comput. 19, 431–448 (2015)
    Google Scholar
  46. Lei, D., Guo, X.: A shuffled frog-leaping algorithm for job shop scheduling with outsourcing options. Int. J. Prod. Res. 54, 1–12 (2016)
    Google Scholar
  47. Huang, X., Wang, J., Wang, L., Gao, W., Wang, X.: Single machine scheduling with time-dependent deterioration and exponential learning effect. Comput. Ind. Eng. 58, 58–63 (2010)
    Google Scholar
  48. Lai, P.J., Wu, C.C., Lee, W.C.: Single-machine scheduling with logarithm deterioration. Optimization Letters 6, 1719–1730 (2012)
    MathSciNet MATH Google Scholar
  49. Rudek, R.: Some single-machine scheduling problems with the extended sum-of-processing-time-based aging effect. Int. J. Adv. Manuf. Technol. 59, 299–309 (2012)
    Google Scholar
  50. Cheng, T.C.E., Tseng, S.C., Lai, P.J., Lee, W.C.: Single-machine scheduling with accelerating deterioration effects. Optimization Letters 8, 543–554 (2014)
    MathSciNet MATH Google Scholar

Download references