Abstract
A dynamic scheduling problem of blocking job shop constrained by machines and workers is studied based on genetic algorithm and simulated annealing algorithm (GASA). The problem is characterized by two resources and no storage buffer, and different disturbances. The objective is to minimize the completing time. The static scheduling results are obtained based on GASA, and the dynamic scheduling results are given according to the disturbance type. Judging whether it is rescheduled or minor adjusted according to the influence to the completing time. If it has little influence to the completion time, try not to disorder the original scheduling result, otherwise, it is rescheduled. When these factors are considered, a more effective schedule result can be obtained based on the method proposed in this paper. The performance of the method is proved based on two cases, and the results show that the method proposed in this paper is effective and feasible.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lu, T., Chen, P., Wan, X.: Improved cellular genetic algorithm for solving the multi-objective flexible job shop scheduling problem. Mod. Manuf. Eng. 11, 41–49 (2016)
Oulamara, A.: Makespan minimization in a no-wait flow shop problem with two batching machines. Comput. Oper. Res. 34, 1033–1050 (2007)
Yan, S., Shi, Y., Chen, B.: Dynamic jobshop scheduling with personalized customization in intelligent manufacturing. J. Southwest Univ. Sci. Technol. 32(2), 84–89 (2017)
Hegera, J., Voss, T.: Optimal scheduling of AGVs in a reentrant blocking job-shop. In: 11th CIRP Conference on Intelligent Computation in Manufacturing Engineering, pp. 41–45 (2018)
Sadaqa, M., Moraga, R.J.: Scheduling blocking flow shops using Meta-RaPS. Procedia Comput. Sci. 61, 533–538 (2015)
Zeng, C., Liu, S.: Job shop scheduling problem with limited output buffer. J. Northeastern Univ. (Nat. Sci.) 39(12), 1679–1684 (2018)
Xie, Z., Zhang, C., Shao, X., et al.: Flow shop scheduling with limited buffer based on memetic algorithm. Comput. Integr. Manuf. Syst. 21(5), 1253–1261 (2015)
Huang, Y., Li, J., Yan, X.: Study on dynamic scheduling of dual resource constrained job shop. Mech. Sci. Technol. Aerosp. Eng. 35(6), 968–974 (2016)
Dhiflaoui, M., Nouri, H.E., Driss, O.B.: Dual-resource constraints in classical and flexible job shop problems: a state-of-the-art review. Procedia Comput. Sci. 126, 1507–1515 (2018)
Li, J., Huang, Y., Niu, X.: A branch population genetic algorithm for dual-resource constrained job shop scheduling problem. Comput. Ind. Eng. 102, 113–131 (2016)
Lei, D., Guo, X.: An effective neighborhood search for scheduling in dual-resource constrained interval jobshop with environmental objective. Int. J. Prod. Econ. 159, 296–303 (2016)
Pezzellaa, F., Morgantia, G., Ciaschettib, G.: Genetic algorithm for the flexible job shop scheduling. Comput. Oper. Res. 35, 3202–3212 (2008)
Ze, T., Zhou, Q.: Study on MS-BHFSP with multi-objective. In: ICNC-FSKD 2017, pp. 319–323 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Tao, Z., Liu, X. (2019). Dynamic Scheduling of Dual-Resource Constrained Blocking Job Shop. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11745. Springer, Cham. https://doi.org/10.1007/978-3-030-27529-7_38
Download citation
DOI: https://doi.org/10.1007/978-3-030-27529-7_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27528-0
Online ISBN: 978-3-030-27529-7
eBook Packages: Computer ScienceComputer Science (R0)