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Fuzziness in the Berth Allocation Problem

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Recent Advances in Computational Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 795))

Abstract

The berth allocation problem (BAP) in a marine terminal container is defined as the feasible berth allocation to the incoming vessels. In this work, we present two models of fuzzy optimization for the continuous and dynamic BAP. The arrival time of vessels are assumed to be imprecise, meaning that the vessel can be late or early up to a threshold allowed. Triangular fuzzy numbers represent the imprecision of the arrivals. The first model is a fuzzy MILP (Mixed Integer Lineal Programming) and allow us to obtain berthing plans with different degrees of precision; the second one is a model of Fully Fuzzy Linear Programming (FFLP) and allow us to obtain a fuzzy berthing plan adaptable to possible incidences in the vessel arrivals. The models proposed has been implemented in CPLEX and evaluated in a benchmark developed to this end. For both models, with a timeout of 60 min, CPLEX find the optimum solution to instances up to 10 vessels; for instances between 10 and 45 vessels it find a non-optimum solution and for bigger instants no solution is founded.

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References

  1. Bierwirth, C., Meisel, F.: A survey of berth allocation and quay crane scheduling problems in container terminals. Eur. J. Oper. Res. 202(3), 615–627 (2010)

    Article  MathSciNet  Google Scholar 

  2. Bruggeling, M., Verbraeck, A., Honig, H.: Decision support for container terminal berth planning: integration and visualization of terminal information. In: Proceedings of the Van de Vervoers logistieke Werkdagen (VLW2011), University Press, Zelzate, pp. 263–283 (2011)

    Google Scholar 

  3. Das, S.K., Mandal, T., Edalatpanah, S.A.: A mathematical model for solving fully fuzzy linear programming problem with trapezoidal fuzzy numbers. Appl. Intell. 46(3), 509–519 (2017)

    Article  Google Scholar 

  4. Exposito-Izquiero, C., Lalla-Ruiz, E., Lamata, T., Melian-Batista, B., Moreno-Vega, J.: Fuzzy optimization models for seaside port logistics: berthing and quay crane scheduling. In: Computational Intelligence, pp. 323–343. Springer International Publishing (2016)

    Google Scholar 

  5. Gutierrez, F., Vergara, E., Rodrguez, M., Barber, F.: Un modelo de optimizacin difuso para el problema de atraque de barcos. Investigacin Operacional 38(2), 160–169 (2017)

    Google Scholar 

  6. Jimenez, M., Arenas, M., Bilbao, A., Rodrı, M.V.: Linear programming with fuzzy parameters: an interactive method resolution. Eur. J. Oper. Res. 177(3), 1599–1609 (2007)

    Article  MathSciNet  Google Scholar 

  7. Kim, K.H., Moon, K.C.: Berth scheduling by simulated annealing. Transp. Res. Part B Methodol. 37(6), 541–560 (2003)

    Article  Google Scholar 

  8. Laumanns, M., et al.: Robust adaptive resource allocation in container terminals. In: Proceedings of the 25th Mini-EURO Conference Uncertainty and Robustness in Planning and Decision Making, Coimbra, Portugal, pp. 501–517 (2010)

    Google Scholar 

  9. Lim, A.: The berth planning problem. Oper. Res. Lett. 22(2), 105–110 (1998)

    Article  MathSciNet  Google Scholar 

  10. Luhandjula, M.K.: Fuzzy mathematical programming: theory, applications and extension. J. Uncertain Syst. 1(2), 124–136 (2007)

    Google Scholar 

  11. Nasseri, S.H., Behmanesh, E., Taleshian, F., Abdolalipoor, M., Taghi-Nezhad, N.A.: Fullyfuzzy linear programming with inequality constraints. Int. J. Ind. Math. 5(4), 309–316 (2013)

    Google Scholar 

  12. Rodriguez-Molins, M., Ingolotti, L., Barber, F., Salido, M.A., Sierra, M.R., Puente, J.: A genetic algorithm for robust berth allocation and quay crane assignment. Prog. Artif. Intell. 2(4), 177–192 (2014)

    Article  Google Scholar 

  13. Rodriguez-Molins, M., Salido, M.A., Barber, F.: A GRASP-based metaheuristic for the Berth Allocation Problem and the Quay Crane Assignment Problem by managing vessel cargo holds. Appl. Intell. 40(2), 273–290 (2014)

    Article  Google Scholar 

  14. Steenken, D., Vo, S., Stahlbock, R.: Container terminal operation and operations research—a classification and literature review. OR Spectr. 26(1), 3–49 (2004)

    Article  Google Scholar 

  15. Wang, X., Kerre, E.E.: Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets Syst. 118(3), 375–385 (2001)

    Article  MathSciNet  Google Scholar 

  16. Yager, R.R.: A procedure for ordering fuzzy subsets of the unit interval. Inf. Sci. 24(2), 143–161 (1981)

    Article  MathSciNet  Google Scholar 

  17. Young-Jou, L., Hwang, C.: Fuzzy Mathematical Programming: Methods and Applications, vol. 394. Springer Science & Business Media (2012)

    Google Scholar 

  18. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 100, 9–34 (1999)

    Article  Google Scholar 

  19. Zimmermann, H.: Fuzzy Set Theory and Its Applications, Fourth Revised Edition. Springer, Berlin (2001)

    Google Scholar 

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Acknowledgements

This work was supported by INNOVATE-PERU, Project N PIBA-2-P-069-14.

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Authors and Affiliations

  1. Department of Mathematics, National University of Piura, Piura, Peru

    Flabio Gutierrez

  2. Department of Informatics, National University of Trujillo, Trujillo, Peru

    Edwar Lujan

  3. Department of Mathematics, National University of Trujillo, Trujillo, Peru

    Rafael Asmat & Edmundo Vergara

Authors
  1. Flabio Gutierrez
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  2. Edwar Lujan
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  3. Rafael Asmat
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  4. Edmundo Vergara
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Corresponding author

Correspondence to Flabio Gutierrez .

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Editors and Affiliations

  1. Department of Parallel Algorithms, Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Stefka Fidanova

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Gutierrez, F., Lujan, E., Asmat, R., Vergara, E. (2019). Fuzziness in the Berth Allocation Problem. In: Fidanova, S. (eds) Recent Advances in Computational Optimization. Studies in Computational Intelligence, vol 795. Springer, Cham. https://doi.org/10.1007/978-3-319-99648-6_9

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