Open Access
Manufacturing Rev.
Volume 1, 2014
Article Number 13
Number of page(s) 13
Published online 09 September 2014
  1. S.M. Johnson, Optimal two and three-stage production schedules with set up times included, Naval Research Logistics Quarterly 1 (1954) 61–68. [CrossRef]
  2. W.H. Yang, A study on the intelligent neural network training using the electromagnetism algorithm, Unpublished Master Thesis, Dept. of Industrial Engineering and Management, I-Shou University, Kaohsiung County, Taiwan, 2002.
  3. R. Ruiz, T. Stützle, An Iterated Greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives, European Journal of Operational Research 187, 3 (2008) 1143–1159. [CrossRef]
  4. M. Khalili, M.J. Tarokh, B. Naderi, Using electromagnetism algorithm for determining the number of kanbans in a multi-stage supply chain system, Journal of Industrial Engineering 6 (2010) 63–72.
  5. P. Wu, W.-H. Yang, N.-C. Wei, An electromagnetism algorithm of neural network analysis – an application to textile retail operation, Journal of the Chinese Institute of Industrial Engineers 21 (2004) 59–67. [CrossRef]
  6. M.S. Salvador, A solution to a special case of flow shop scheduling problems, in: S.E. Elmaghraby (Ed.), Symposium of the Theory of Scheduling and its Applications, Springer, New York, 1973, pp. 83–91. [CrossRef]
  7. R. Linn, W. Zhang, Hybrid flow shop scheduling: a survey, Computers & Industrial Engineering 37, 1–2 (1999) 57–61. [CrossRef]
  8. H. Wang, Flexible flowshop scheduling: optimum, heuristics, and artificial intelligence solutions, Expert Systems 22, 2 (2005) 78–85. [CrossRef]
  9. O. Moursli, Y. Pochet, A branch-and-bound algorithm for the hybrid flowshop, International Journal of Production Economics 64, 1–3 (2000) 113–125. [CrossRef]
  10. C. Sriskandarajah, S.P. Sethi, Scheduling algorithms for flexible flowshops: worst and average case performance, European Journal of Operational Research 43, 2 (1989) 143–160. [CrossRef] [MathSciNet]
  11. A. Guinet, M.M. Solomon, P.K. Kedia, A. Dussauchoy, A computational study of heuristics for two-stage flexible flowshops, International Journal of Production Research 34, 5 (1996) 1399–1415. [CrossRef]
  12. E. Nowicki, C. Smutnicki, The flow shop with parallel machines: a tabu search approach, European Journal of Operational Research 106, 2–3 (1998) 226–253. [CrossRef]
  13. M. Gourgand, N. Grangeon, S. Norre, Metaheuristics for the deterministic hybrid flow shop problem, Proceeding of the International Conference on Industrial Engineering and Production Management (IEPM’99), Glasgow, United Kingdom, July 12–15 (1999), pp. 136–145.
  14. R. Zhang, C. Wu, A simulated annealing algorithm based on block properties for the job shop scheduling problem with total weighted tardiness objective, Computers & Operations Research 38 5 (2011) 854–867. [CrossRef] [MathSciNet]
  15. C.R. Reeves, A genetic algorithm for flowshop sequencing, Computers & Operations Research 22, 1 (1995) 5–13. [CrossRef]
  16. R. Tavakkoli-Moghaddam, N. Safaei, F. Sassani, A memetic algorithm for the flexible flow line scheduling problem with processor blocking, Computers & Operations Research 36 (2009) 402–414. [CrossRef] [MathSciNet]
  17. R. Cheng, M. Gen, M. Tozawa, Minmax earliness/tardiness scheduling in identical parallel machine system using genetic algorithms, Computers & Industrial Engineering 29, 1–4 (1995) 513–517. [CrossRef]
  18. J. Yang, Minimizing total completion time in two-stage hybrid flow shop with dedicated machines, Computers & Operations Research 38, 7 (2011) 1045–1053. [CrossRef] [MathSciNet]
  19. M. Khalili, R. Tavakoli-Moghadam, A multi-objective electromagnetism algorithm for a bi-objective flowshop scheduling problem, Journal of Manufacturing Systems 31 (2012) 232–239. [CrossRef]
  20. C. Chen, R. Neppalli, Genetic algorithms applied to the continuous flow shop problem, Computers & Industrial Engineering 30, 4 (1996) 919–929. [CrossRef]
  21. T. Aldowaisan, A. Allahverdi, New heuristics for m-machine no-wait flowshop to minimize total completion time, Omega 32, 5 (2004) 345–352. [CrossRef]
  22. Q.K. Pan, M.F. Tasgetiren, Y.C. Liang, A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem, Computers & Operations Research 35 (2008) 2807–2839. [CrossRef] [MathSciNet]
  23. A. Fink, S. Voß, Solving the continuous flow-shop scheduling problem by metaheuristics, European Journal of Operational Research 151 (2003) 400–414. [CrossRef] [MathSciNet]
  24. S.J. Shyu, B.M.T. Lin, P.Y. Yin, Application of ant colony optimization for no-wait flowshop scheduling problem to minimize the total completion time, Computers & Industrial Engineering 47 (2004) 181–193. [CrossRef]
  25. J. Grabowski, J. Pempera, Some local search algorithms for no-wait flow-shop problem with makespan criterion, Computers & Operations Research 32 (2005) 2197–2212. [CrossRef] [MathSciNet]
  26. M. Khalili, An iterated local search algorithm for flexible flow lines with sequence dependent setup times to minimize total weighted completion, International Journal of Management Science and Engineering Management 7, 1 (2012) 63–66.
  27. M. Khalili, Multi-objective no-wait hybrid flowshop scheduling problem with transportation times, Journal International Journal of Computational Science and Engineering 7, 2 (2012) 147–153.
  28. J. Hurink, S. Knust, Makespan minimization for flow-shop problems with transportation times and a single robot, Discrete Applied Mathematics 112 (2001) 199–216. [CrossRef] [MathSciNet]
  29. A. Soukhal, A. Oulamara, P. Martineau, Complexity of flow shop scheduling problems with transportation constraints, European Journal of Operational Research 161 (2005) 32–41. [CrossRef] [MathSciNet]
  30. R. Ruiz, C.J. Garica-Diaz, C. Maroto, Considering scheduling and preventive maintenance in the flowshop sequencing problem, Computers & Operations Research 34 (2007) 3314–3330. [CrossRef]
  31. G. Schmidt, Scheduling with limited machine availability, European Journal of Operational Research 121 (2000) 1–15. [CrossRef] [MathSciNet]
  32. C.Y. Lee, Minimizing the makespan in the two-machine flowshop scheduling problem with an availability constraint, Operations Research Letters 20 (1997) 129–139. [CrossRef] [MathSciNet]
  33. J. Blazewicz, J. Breit, P. Formanowicz, W. Kubiak, G. Schmidt, Heuristic algorithms for the two-machine flowshop problem with limited machine availability, Omega 29 (2001) 599–608. [CrossRef]
  34. J. Breit, A polynomial-time approximation scheme for the two-machine flow shop scheduling problem with an availability constraint, Computers & Operations Research 33 (2006) 2143–2153. [CrossRef] [MathSciNet]
  35. H. Allaoui, A. Artiba, Integrating simulation and optimization to scheduling a hybrid flow shop with maintenance constraints, Computers & Industrial Engineering 47 (2004) 431–450. [CrossRef]
  36. V. Cerny, Thermodynamical approach to the travelling salesman problem: an efficient simulation algorithm, JOTA 45 (1985) 41–51. [CrossRef] [MathSciNet]
  37. I. Birbil, S.C. Fang, An electromagnetism-like mechanism for global optimization, Journal of Global Optimization 25 (2003) 263–282. [CrossRef] [MathSciNet]
  38. D. Debels, B.D. Reyck, R. Leus, M. Vanhoucke, A hybrid scatter search/electromagnetism meta-heuristic for project scheduling, European Journal of Operational Research 169 (2006) 638–653. [CrossRef] [MathSciNet]
  39. E. Taillard, Benchmarks for basic scheduling problems, European Journal of Operational Research 64, 2 (1993) 278–285. [CrossRef]
  40. R. Ruiz, A. Allahverdi, Some effective heuristics for no-wait flowshops with setup times to minimize total completion time, Annals of Operation Research 156 (2007) 143–171. [CrossRef]
  41. B. Naderi, M. Mousakhani, M. Khalili, Scheduling multi-objective open shop scheduling using a hybrid immune algorithm, The International Journal of Advanced Manufacturing Technology 66, 5–8 (2013) 895–905. [CrossRef]
  42. D.C. Montgomery, Design and Analysis of Experiments, Fifth edition, John Wiley & Sons, 2000.

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