Advertisement

Using CSP Solvers as Alternative to Simulation Optimization Engines

  • Pawel PawlewskiEmail author
  • Marcin Anholcer
Chapter
Part of the EcoProduction book series (ECOPROD)

Abstract

This paper describes the results in the area of modeling and simulation of the milk-run systems in assembly plants. We propose a hybrid solution in order to show how the simulation and optimization can be combined to make such systems more efficient. The paper describes the preliminary results of the research that will be developed in the future.

Keywords

Hybrid modeling approach Simulation Logistics systems Tugger train scheduling with time windows Optimization Mathematical modeling 

Notes

Acknowledgements

The work was carried out as part of the POIR.01.01.01-00-0485/17 project, “Development of a new type of logistic trolley and methods of collision-free and deadlock-free implementation of intralogistics processes”, financed by NCBiR.

References

  1. 1.
    Alnahhal, M., Noche, B.: Dynamic material flow control in mixed model assembly lines. Comput. Ind. Eng. 85, 110–119 (2015)CrossRefGoogle Scholar
  2. 2.
    Amaran, S, Sahinidis, N.V., Sharda, B, Bury, S.J.: Simulation optimization: a review of algorithms and applications. 4OR-Q. J. Oper. Res. 12(4), 301–333 (2014)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Atres (2018). http://atres.pl/en/log-abs-en. Accessed 25 July 2018
  4. 4.
    Beaverstock, M., Greenwood, A., Nordgren, W.: Applied Simulation: Modeling and Analysis using Flexsim. Flexsim Software Products Inc., Canyon Park Technology Center, Orem, USA (2017)Google Scholar
  5. 5.
    Boysen, N., Emde, S.: Scheduling the part supply of mixed-model assembly lines in line-integrated supermarkets. Eur. J. Oper. Res. 239, 820–829 (2014)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Chau, M., Fu, M.C., Qu, H., Ryzhov, I.O.: Simulation optimization: a tutorial overview and recent developments in gradient-based methods. In: Tolk, A., Diallo, S.Y., Ryzhov, I.O., Yilmaz, L., Buckley, S., Miller, J.A. (eds.) Proceedings of the Winter Simulation Conference 2014, pp. 21–35 (2014)Google Scholar
  7. 7.
    Emde, S.: Scheduling the replenishment of just-in-time supermarkets in assembly plants. OR Spectr. 39, 321–345 (2017)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Emde, S., Boysen, N.: Optimally routing and scheduling tow trains for JIT-supply of mixed-model assembly lines. Eur. J. Oper. Res. 217, 287–299 (2012)MathSciNetzbMATHGoogle Scholar
  9. 9.
    Emde, S., Gendreau, M.: Scheduling in-house transport vehicles to feed parts to automotive assembly lines. Eur. J. Oper. Res. 260, 255–267 (2017)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Eskandari, H., Mahmoodi, E., Fallah, H., Geiger, C.D.: Performance analysis of comercial simulation-based optimization packages: OptQuest and witness optimizer. In: Jain, S., Creasey, R., Himmelspach, J., White, K.P., Fu, M.C. (eds.) Proceedings of the 2011 Winter Simulation Conference, Phoenix, AZ, USA, pp. 2363–2373 (2011)Google Scholar
  11. 11.
    Fu, M.C.: Optimization for simulation: theory vs. practice. INFORMS J. Comput. 14(3), 192–215 (2002)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Golz, J., Gujjula, R., Günther, H.-O., Rinderer, S., Ziegler, M.: Part feeding at high-variant mixed-model assembly lines. Flex. Serv. Manuf. J. 24, 119–141 (2012)CrossRefGoogle Scholar
  13. 13.
    Kilic, H.S., Durmusoglu, M.B.: A mathematical model and a heuristic approach for periodic material delivery in lean production environment. Int. J. Adv. Manuf. Technol. 69, 977–992 (2013)CrossRefGoogle Scholar
  14. 14.
    Kilic, H.S., Durmusoglu, M.B., Baskak, M.: Classification and modeling for in-plant milk-run distribution systems. Int. J. Adv. Manuf. Technol. 62, 1135–1146 (2012)CrossRefGoogle Scholar
  15. 15.
    Law, A.M.: Simulation Modeling and Analysis, 4th edn. McGraw-Hill, New York (2007)Google Scholar
  16. 16.
    Olafsson, S., Kim, J.: Simulation optimization. In: Yücesan, E., Chen, C.H., Snowdon, J.L., Charnes, J.M. (eds.) Proceedings of the 2002 Winter Simulation Conference, San Diego, CA, USA, pp. 79–84 (2002)Google Scholar
  17. 17.
    Satoglu, S.I., Sahin, I.E.: Design of a just-in-time periodic material supply system for the assembly lines and an application in electronics industry. Int. J. Adv. Manuf. Technol. 65, 319–332 (2013)CrossRefGoogle Scholar
  18. 18.
    Schneider, M.: The vehicle-routing problem with time windows and driver-specific times. Eur. J. Oper. Res. 250, 101–119 (2016)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Vaidyanathan, B.S., Matson, J.O., Miller, D.M., Matson, J.E.: A capacitated vehicle routing problem for just-in-time delivery. IIE Trans. 31, 1083–1092 (1999)Google Scholar
  20. 20.
    Zenker, M., Emde, S., Boysen, N.: Cyclic inventory routing in a line-shaped network. Eur. J. Oper. Res. 250, 164–178 (2016)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Poznan University of TechnologyPoznańPoland
  2. 2.Poznan University of Economics and BusinessPoznańPoland

Personalised recommendations