Open Access
Issue |
RAIRO-Oper. Res.
Volume 55, Number 3, May-June 2021
|
|
---|---|---|
Page(s) | 1603 - 1616 | |
DOI | https://doi.org/10.1051/ro/2021076 | |
Published online | 15 June 2021 |
- P. Alfaro-Fernàndez, R. Ruiz, F. Pagnozzi and T. Stützle, Automatic algorithm design for hybrid flowshop scheduling problems., Eur. J. Oper. Res. 282 (2020) 835–845. [CrossRef] [Google Scholar]
- S. Aqil and K. Allali, Two efficient nature inspired meta-heuristics solving blocking hybrid flow shop manufacturing problem. Eng. Appl. Artif. Intell. 100 (2021) 104196. [CrossRef] [Google Scholar]
- T. Bartz-Beielstein, M. Chiarandini, L. Paquete and M. Preuss, Experimental Methods for the Analysis of Optimization Algorithms. Springer (2010). [CrossRef] [Google Scholar]
- A. Elmi and S. Topaloglu, A scheduling problem in blocking hybrid flow shop robotic cells with multiple robots. Comput. Oper. Res. 40 (2013) 2543–2555. [CrossRef] [MathSciNet] [Google Scholar]
- O. Engin and A. Döyen, A new approach to solve hybrid flow shop scheduling problems by artificial immune system. Future Gener. Comput. Syst. 20 (2004) 1083–1095. [CrossRef] [Google Scholar]
- L. Fanjul-Peyro and R. Ruiz, Iterated greedy local search methods for unrelated parallel machine scheduling. Eur. J. Oper. Res. 207 (2010) 55–69. [CrossRef] [Google Scholar]
- J.M. Framinan, R. Leisten and R.R. García, Manufacturing scheduling systems. In: An Integrated View on Models, Methods and Tools (2014) 51–63. [Google Scholar]
- J. Grabowski and J. Pempera, Nowy algorytm tabu search dla zagadnienia kolejnościowego przep lywowego. Automatyka/Akademia Górniczo-Hutnicza im. Stanis lawa Staszica w Krakowie 3 (1999) 125–133. [Google Scholar]
- R.L. Graham, E.L. Lawler, J.K. Lenstra and A.R. Kan, Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann. Discrete Math. 5 (1979) 287–326. [CrossRef] [MathSciNet] [Google Scholar]
- N.G. Hall and C. Sriskandarajah, A survey of machine scheduling problems with blocking and no-wait in process. Oper. Res. 44 (1996) 510–525. [CrossRef] [MathSciNet] [Google Scholar]
- L. Hidri and M. Haouari, Bounding strategies for the hybrid flow shop scheduling problem. Appl. Math. Comput. 217 (2011) 8248–8263. [Google Scholar]
- X.-L. Jing, Q.-K. Pan, L. Gao and Y.-L. Wang, An effective iterated greedy algorithm for the distributed permutation flowshop scheduling with due windows. Appl. Soft Comput. 96 (2020) 106629. [CrossRef] [Google Scholar]
- C. Kahraman, O. Engin, I. Kaya and M. Kerim Yilmaz, An application of effective genetic algorithms for solving hybrid flow shop scheduling problems. Int. J. Comput. Intell. Syst. 1 (2008) 134–147. [CrossRef] [Google Scholar]
- A. Khare and S. Agrawal, Scheduling hybrid flowshop with sequence-dependent setup times and due windows to minimize total weighted earliness and tardiness. Comput. Ind. Eng. 135 (2019) 780–792. [CrossRef] [Google Scholar]
- G. Lebbar, I. El Abbassi, A. El Barkany, A. Jabri and M. Darcherif, Solving the multi objective flow shop scheduling problems using an improved nsga-ii. Int. J. Oper. Quant. Manage. 24 (2018) 211–230. [Google Scholar]
- D. Lei, Co-evolutionary genetic algorithm for fuzzy flexible job shop scheduling. Appl. Soft Comput. 12 (2012) 2237–2245. [CrossRef] [Google Scholar]
- J.V. Moccellin, M.S. Nagano, A.R.P. Neto and B. de Athayde Prata, Heuristic algorithms for scheduling hybrid flow shops with machine blocking and setup times. J. Braz. Soc. Mech. Sci. Eng. 40 (2018) 40. [CrossRef] [Google Scholar]
- B. Naderi, M. Zandieh, A.K.G. Balagh and V. Roshanaei, An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness. Expert Syst. Appl. 36 (2009) 9625–9633. [Google Scholar]
- M.H. Newton, V. Riahi, K. Su and A. Sattar, Scheduling blocking flowshops with setup times via constraint guided and accelerated local search. Comput. Oper. Res. 109 (2019) 64–76. [CrossRef] [Google Scholar]
- Q.-K. Pan, L. Wang, K. Mao, J.-H. Zhao and M. Zhang, An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process. IEEE Trans. Autom. Sci. Eng. 10 (2012) 307–322. [CrossRef] [Google Scholar]
- Q.-K. Pan, L. Gao, X.-Y. Li and K.-Z. Gao, Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times. Appl. Math. Comput. 303 (2017) 89–112. [Google Scholar]
- Q.-K. Pan, R. Ruiz and P. Alfaro-Fernàndez, Iterated search methods for earliness and tardiness minimization in hybrid flowshops with due windows. Comput. Oper. Res. 80 (2017) 50–60. [CrossRef] [Google Scholar]
- F. Pezzella, G. Morganti and G. Ciaschetti, A genetic algorithm for the flexible job-shop scheduling problem. Comput. Oper. Res. 35 (2008) 3202–3212. [CrossRef] [Google Scholar]
- C.N. Potts and L.N. Van Wassenhove, A decomposition algorithm for the single machine total tardiness problem. Oper. Res. Lett. 1 (1982) 177–181. [CrossRef] [Google Scholar]
- M. Pranzo and D. Pacciarelli, An iterated greedy metaheuristic for the blocking job shop scheduling problem. J. Heurist. 22 (2016) 587–611. [CrossRef] [Google Scholar]
- E. Rashidi, M. Jahandar and M. Zandieh, An improved hybrid multi-objective parallel genetic algorithm for hybrid flow shop scheduling with unrelated parallel machines. Int. J. Adv. Manuf. Technol. 49 (2010) 1129–1139. [CrossRef] [Google Scholar]
- I. Ribas, R. Companys and X. Tort-Martorell, An iterated greedy algorithm for the flowshop scheduling problem with blocking. Omega 39 (2011) 293–301. [CrossRef] [Google Scholar]
- I. Ribas, R. Companys and X. Tort-Martorell, An iterated greedy algorithm for solving the total tardiness parallel blocking flow shop scheduling problem. Expert Syst. Appl. 121 (2019) 347–361. [CrossRef] [Google Scholar]
- R. Ruiz and T. Stützle, A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. Eur. J. Oper. Res. 177 (2007) 2033–2049. [CrossRef] [Google Scholar]
- R. Ruiz and J.A. Vàzquez-Rodríguez, The hybrid flow shop scheduling problem. Eur. J. Oper. Res. 205 (2010) 1–18. [CrossRef] [Google Scholar]
- R. Ruiz, Q.-K. Pan and B. Naderi, Iterated greedy methods for the distributed permutation flowshop scheduling problem. Omega 83 (2019) 213–222. [CrossRef] [Google Scholar]
- T.J. Sawik, A scheduling algorithm for flexible flow lines with limited intermediate buffers. Appl. Stoch. Models Data Anal. 9 (1993) 127–138. [CrossRef] [Google Scholar]
- M.F. Tasgetiren, D. Kizilay, Q.-K. Pan and P.N. Suganthan, Iterated greedy algorithms for the blocking flowshop scheduling problem with makespan criterion. Comput. Oper. Res. 77 (2017) 111–126. [CrossRef] [Google Scholar]
- W. Trabelsi, C. Sauvey and N. Sauer, A genetic algorithm for hybrid flowshop problem with mixed blocking constraints. In: IFAC Conference on Manufacturing, Modelling, Management and Control (2013). [Google Scholar]
- K. Yuan, N. Sauer and C. Sauvey, Application of em algorithm to hybrid flow shop scheduling problems with a special blocking. In: 2009 IEEE Conference on Emerging Technologies & Factory Automation. IEEE (2009) 1–7. [Google Scholar]
- Q. Zeng and Z. Yang, A hbrid flow shop scheduling model for loading outbound containers in container terminals. In: Proceedings of the Eastern Asia Society for Transportation Studies Vol. 6 (The 7th International Conference of Eastern Asia Society for Transportation Studies, 2007). Eastern Asia Society for Transportation Studies (2007) 381. [Google Scholar]
- Y. Zhang, X. Liang, W. Li and Y. Zhang, Hybrid flow shop problem with blocking and multi-product families in a maritime terminal. In: 2013 10th IEEE International Conference on Networking, Sensing and Control (ICNSC). IEEE (2013) 59–64. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.