Annals of Operations Research

, Volume 264, Issue 1–2, pp 409–433 | Cite as

Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry

  • Miguel A. Ortíz
  • Leidy E. Betancourt
  • Kevin Parra Negrete
  • Fabio De Felice
  • Antonella Petrillo
Original Paper
  • 129 Downloads

Abstract

In today highly competitive and globalized markets, an efficient use of production resources is necessary for manufacturing enterprises. In this research, the problem of scheduling and sequencing of manufacturing system is presented. A flexible job shop problem sequencing problem is analyzed in detail. After formulating this problem mathematically, a new model is proposed. This problem is not only theoretically interesting, but also practically relevant. An illustrative example is also conducted to demonstrate the applicability of the proposed model.

Keywords

Sequencing problem Flexible job-shop system Reconfigurable system Optimization 

Nomenclature

n

Number of pieces

m

Number of machines

G(i)

Number of operations of the piece i (i = 1...n)

H(j)

Number of operations in the tail of the machine j (j = 1 ...m).

fj

Instant the machine j is available for a new operation

pk,i,j

Processing time of operation k of the item i in the machine j

rk,i

Instant availability of operation (k, i)

Rpk,i,j

(release date o ready date) Early instant to start the operation (k, i) on the machine j: \(\hbox {rpk,i,j }= \hbox {max }\{\hbox { rk,i, fj for all (k,i) }\upepsilon \hbox { Ej}\)

fpj

Early instant to start a new operation on the machine j (if no queue, infinite value is assigned):

\(\hbox {fpj} = \hbox {min(k,i)}\upepsilon \hbox { Ej }\{\hbox { rpk,i,j }\}\) if Ej is not empty

\(\hbox {fpj} = \infty \) if Ej is empty

\(\hbox {t}_{\mathrm{start}}\) (k, i)

Manufacturing start time scheduled operation

[\(\hbox {t}_{\mathrm{start}}\)] \(\hbox {(k, i)} = \hbox {rpk,i, j}\)

\(\hbox {t}_{\mathrm{end}}\) (k, i)

Manufacturing final instant programmed operation

[\(\hbox {t}_{\mathrm{end}}\)] \(\hbox {(k, i)} = \hbox {tstart (k, i)} +\hbox { D }\cdot \hbox { pk,i,j}\)

References

  1. Alvarez-Valdes, R., Fuertes, A., Tamarit, J. M., Giménez, G., & Ramos, R. (2005). A heuristic to schedule flexible job-shop in a glass factory. European Journal of Operational Research, 165(2005), 525–534.CrossRefGoogle Scholar
  2. Baker, K. R. (2005). Elements of sequencing and scheduling. Hanover, NH: Tuck School of Business.Google Scholar
  3. Barrios, M. A. O., Caballero, J. E., & Sánchez, F. S. (2015). A methodology for the creation of integrated service networks in outpatient internal medicine. In Ambient intelligence for health (pp. 247–257). Springer.Google Scholar
  4. Bozek, A., & Wysocki, M. (2015). Flexible job shop with continuous material flow. International Journal of Production Research, 53(4), 1273–1290.CrossRefGoogle Scholar
  5. Brandimarte, P. (1993). Routing and scheduling in a flexible job shop by Tabu search. Annals of Operations Research, 41(3), 157–183.CrossRefGoogle Scholar
  6. Calleja, G., & Pastor, R. (2014). A dispatching algorithm for flexible job-shop scheduling with transfer batches: An industrial application. Production Planning & Control, 25(2), 93–109.CrossRefGoogle Scholar
  7. De Felice, F., & Petrillo, A. (2013). Simulation approach for the optimization of the layout in a manufacturing firm. 24th IASTED international conference on modelling and simulation, MS 2013; Banff, AB; Canada; 17 July 2013 through 19 July 2013 (pp. 152–161).Google Scholar
  8. Demir, Y., & Işleyen, S. K. (2014). An effective genetic algorithm for flexible job-shop scheduling with overlapping in operations. International Journal of Production Research, 52(13), 3905–3921.CrossRefGoogle Scholar
  9. Digiesi, S., Mossa, G., & Mummolo, G. (2013). A sustainable order quantity model under uncertain product demand. 7th IFAC conference on manufacturing modelling, management, and control, MIM 2013 (pp. 664–669). Saint Petersburg; Russian Federation; 19 June–21 June.Google Scholar
  10. Fattahi, F., & Fallahi, A. (2010). Dynamic scheduling in flexible job shop systems by considering simultaneously efficiency and stability. CIRP Journal of Manufacturing Science and Technology, 2, 114–123.CrossRefGoogle Scholar
  11. Fattahi, P., Hosseini, S. M. H., Jolai, F., & Tavakkoli-Moghaddam, R. (2014). A branch and bound algorithm for hybrid flow shop scheduling problem with setup time and assembly operations. Applied Mathematical Modelling, 38, 119–134.CrossRefGoogle Scholar
  12. Gholami, O., & Sotskov, Y. N. (2014). Solving parallel machines job-shop scheduling problems by an adaptive algorithm. International Journal of Production Research, 52(13), 3888–3904.CrossRefGoogle Scholar
  13. Guo, W. J. (2006). Algorithms for two-stage flexible flow shop scheduling with fuzzy processing times. NanJing: NanJing University of Science & Technology.Google Scholar
  14. Hassin, R., & Shani, M. (2005). Machine scheduling with earliness, tardiness and nonexecution penalties. Computers & Operations Research, 32, 683–705.CrossRefGoogle Scholar
  15. Herazo-Padilla, N., Montoya-Torres, J. R., Isaza, S. N., & Alvarado-Valencia, J. (2015). Simulation-optimization approach for the stochastic location-routing problem. Journal of Simulation, 9(4), 296–311.CrossRefGoogle Scholar
  16. Hildebrandt, T., Heger, J., & Scholz-Reiter, B. (2010). Towards improved dispatching rules for complex shop floor scenarios—A genetic programming approach. GECCO’10, July 7–11, 2010. Portland, Oregon, USA.Google Scholar
  17. Hu, H. (2015). Adaptive scheduling model in hybrid flowshop production control using petri net. International Journal of Control and Automation, 8(1), 233–242.CrossRefGoogle Scholar
  18. Jansen K, Mastrolilli M, & Solis-Oba R, (2000). Approximation algorithms for Flexible Job Shop Problems. In: Lecture notes in computer science, Vol. 1776. Proceedings of the fourth Latin American symposium on theoretical informatics (pp. 68–77). Berlin: Springer.Google Scholar
  19. Jungwattanakit, J., Reodecha, M., Chaovalitwongse, P., & Werner, F. (2009). A comparison of scheduling algorithms for flexible flow shop problems with unrelated parallel machines, setup times, and dual criteria. Computers and Operations Research, 36(2), 358–378.CrossRefGoogle Scholar
  20. Kacem, I., Hammadi, S., & Borne, P. (2002). Pareto-optimality Approach for Flexible Job-shop Scheduling Problems: Hybridization of Evolutionary Algorithms and Fuzzy Logic. Journal of Mathematics and Computers in Simulation Google Scholar
  21. Karimi-Nasab, M., & Modarres, M. (2015). Lot sizing and job shop scheduling with compressible process times: A cut and branch approach. Computers & Industrial Engineering, 85, 196–205.CrossRefGoogle Scholar
  22. Kurz, M. E., & Askin, R. G. (2004). Scheduling flexible flow lines with sequence dependent setup times. European Journal of Operational Research, 159(1), 66–82.CrossRefGoogle Scholar
  23. Logendran, R., Carson, S., & Hanson, E. (2005). Grouping scheduling in flexible flow shops. International Journal of Production Economics, 96(2), 143–155.CrossRefGoogle Scholar
  24. Pezzella, F., Morganti, G., & Ciaschetti, G. (2008). A genetic algorithm for the Flexible Job-shop Scheduling Problem. Computers & Operations Research, 35, 3202–3212.CrossRefGoogle Scholar
  25. Pinedo, M. (2001). Scheduling: Theory, algorithms, and systems. Upper Saddle River, NJ: Prentice Hall.Google Scholar
  26. Prot, D., Bellenguez-Morineau, O., & Lahlou, C. (2013). New complexity results for parallel identical machine scheduling problems with preemption, release dates and regular criteria. European Journal of Operational Research, 231, 282–287.CrossRefGoogle Scholar
  27. Riane, F., Artiba, A., & Elmaghraby, S. E. (2002). Sequencing a hybrid two-stage flow shop with dedicated machines. Int. J. Prod. Res., 40, 4353–4380.CrossRefGoogle Scholar
  28. Shen, X.-N., & Yao, X. (2015). Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems. Information Sciences, 298, 198–224.CrossRefGoogle Scholar
  29. Sotskov, Y. N., & Gholami, O. (2015). Mixed graph model and algorithms for parallel-machine job-shop scheduling problems. International Journal of Production Research, 55(6), 1549–1564.CrossRefGoogle Scholar
  30. Sun, D.-H., He, W., Zheng, L.-J., & Liao, X.-Y. (2014). Scheduling flexible job shop problem subject to machine breakdown with game theory. International Journal of Production Research, 52(13), 3858–3876.CrossRefGoogle Scholar
  31. Türkylmaz, A., & Bulkan, S. (2015). A hybrid algorithm for total tardiness minimization in flexible job shop: Genetic algorithm with parallel VNS execution. International Journal of Production Research, 53(6), 1832–1848.CrossRefGoogle Scholar
  32. Wang, S., & Liu, M. (2013). A heuristic method for two-stage hybrid flow shop with dedicated machines. Computers & Operations Research, 40, 438–450.CrossRefGoogle Scholar
  33. Yokoyama, M. (2004). Scheduling for two-stage production system with setup and assembly operations. Computers & Operations Research, 31, 2063–2078.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Miguel A. Ortíz
    • 1
  • Leidy E. Betancourt
    • 1
  • Kevin Parra Negrete
    • 1
  • Fabio De Felice
    • 2
  • Antonella Petrillo
    • 3
  1. 1.Department of Industrial EngineeringUniversidad de la Costa CUCBarranquillaColombia
  2. 2.Department of Civil and Mechanical EngineeringUniversity of Cassino and Southern LazioCassinoItaly
  3. 3.Department of EngineeringUniversity of Naples “Parthenope”NaplesItaly

Personalised recommendations