DOTSIM - A Simulation-based Optimization Methodology for the Optimal Duplication Sequence on Freight Transportation Systems

Heygon Araujo, Samyr Vale

2017

Abstract

The definition of the best sequence on route duplication of freight systems consists of a complex NP-hard problem. There exists a huge variety of meta-heuristics (MH) capable of generating satisfactory solutions. However, it is fastidious to know which MH will produce the best solution for a Duplication Sequence Problem (DSP). This paper proposes a process development methodology which guides to evaluate the best duplication sequence comparing the MH's performance with existing approaches such as linear analytical method (LAM). The potential of this methodology is demonstrated by a case study in railways.

References

  1. Ara újo, H. F. H. (2013). Utilizac¸a˜o de ferramentas de simulac¸a˜o para analise de capacidade e dimensionamento material rodante da efc.
  2. Barros, J. (2013). Avaliac¸a˜o dos principais métodos analíticos de c álculo de capacidade de tráfego utilizados em ferrovia nacional e internacional. PhD thesis, Dissertac¸a˜o de Mestrado-UFMG, Minas Gerais.
  3. BRINA, H. L. (1982). Estradas de ferro, volume i e ii. Rio de Janeiro, LTC: Livros Técnicos e Científicos Editora SA.
  4. Davis, L. (1985). Job shop scheduling with genetic algorithms. In Proceedings of an international conference on genetic algorithms and their applications, volume 140. Carnegie-Mellon University Pittsburgh, PA.
  5. de Freitas Filho, P. J. (2001). Introduc¸a˜o à modelagem e simulac¸a˜o de sistemas: com aplicac¸o˜es em Arena. Visual Books.
  6. Fourman, M. P. (1985). Compaction of symbolic layout using genetic algorithms. In Proceedings of the 1st international conference on genetic algorithms, pages 141-153. L. Erlbaum Associates Inc.
  7. Fu, M. C. (1994). Optimization via simulation: A review. Annals of Operations Research, 53(1):199-247.
  8. Fu, M. C. (2002). Optimization for simulation: Theory vs. practice. INFORMS Journal on Computing, 14(3):192-215.
  9. Gendreau, M. and Potvin, J.-Y. (2010). Handbook of metaheuristics, volume 2. Springer.
  10. Glover, F. (1986). Future paths for integer programming and links to artificial intelligence. Computers & Operations Research, 13(5):533-549.
  11. Kang, L., Zhu, X., Wu, J., Sun, H., Siriya, S., and Kanokvate, T. (2014). Departure time optimization of last trains in subway networks: mean-variance model and gsa algorithm. Journal of Computing in Civil Engineering, 29(6):04014081.
  12. Kraft, E. R. (1982). Jam capacity of single track rail lines. In Proceedings of the Transportation Research Forum, volume 23.
  13. Kroon, L., Maróti, G., Helmrich, M. R., Vromans, M., and Dekker, R. (2008). Stochastic improvement of cyclic railway timetables. Transportation Research Part B: Methodological, 42(6):553-570.
  14. Krueger, H., Vaillancourt, E., Drummie, A. M., Vucko, S. J., and Bekavac, J. (2000). Simulation within the railroad environment. In Proceedings of the 32nd conference on Winter simulation, pages 1191-1200. Society for Computer Simulation International.
  15. Pegden, C. D., Sadowski, R. P., and Shannon, R. E. (1995). Introduction to simulation using SIMAN. McGrawHill, Inc.
  16. Rice, J. R. (1976). The algorithm selection problem. Advances in Computers, 15:65-118.
  17. Rossetti, M. D. (2008). Java simulation library (jsl): an open-source object-oriented library for discrete-event simulation in java. International Journal of Simulation and Process Modelling, 4(1):69-87.
  18. Wolpert, D. H. and Macready, W. G. (1997). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1):67-82.
  19. Wu, J., Kang, L., Sun, H., and Jia, X. (2012). Track allocation optimization in railway station: mean-variance model and case study. Journal of Transportation Engineering, 139(5):540-547.
  20. Zhao, F. and Zeng, X. (2006). Simulated annealing-genetic algorithm for transit network optimization. Journal of Computing in Civil Engineering, 20(1):57-68.
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Paper Citation


in Harvard Style

Araujo H. and Vale S. (2017). DOTSIM - A Simulation-based Optimization Methodology for the Optimal Duplication Sequence on Freight Transportation Systems . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-248-6, pages 459-466. DOI: 10.5220/0006337404590466


in Bibtex Style

@conference{iceis17,
author={Heygon Araujo and Samyr Vale},
title={DOTSIM - A Simulation-based Optimization Methodology for the Optimal Duplication Sequence on Freight Transportation Systems},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2017},
pages={459-466},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006337404590466},
isbn={978-989-758-248-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - DOTSIM - A Simulation-based Optimization Methodology for the Optimal Duplication Sequence on Freight Transportation Systems
SN - 978-989-758-248-6
AU - Araujo H.
AU - Vale S.
PY - 2017
SP - 459
EP - 466
DO - 10.5220/0006337404590466