Abstract
Due to the increasing demand for ships carrying containers, the Berth Allocation Problem (BAP) can be considered as a major optimization problem in marine terminals. In this context, we propose a heuristic to solve a continuous case of the BAP. This heuristic is based on the application of the Clustering Search (CS) method with the Simulated Annealing (SA) metaheuristic. The results obtained by CS are compared to other methods found in the literature and its competitiveness is verified.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Barros, V.H., Costa, T.S., Oliveira, A.C.M., Lorena, L.A.N.: Model and heuristic for berth allocation in tidal bulk ports with stock level constraints. Computers & Industrial Engineering 60, 606–613 (2011)
Bierwirth, C., Meisel, F.: A survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research 202(3), 615–627 (2010)
Buhrkal, K., Zuglian, S., Ropke, S., Larsen, J., Lusby, R.: Models for the discrete berth allocation problem: a computational comparison. Transportation Research Part E: Logistics and Transportation Review 47, 461–473 (2011)
Chaves, A.A., Lorena, L.A.N.: Hybrid evolutionary algorithm for the capacitated centered clustering problem. Expert Systems with Applications 38(5), 5013–5018 (2010)
Cheong, C.Y., Tan, K.C., Liu, D.K., Lin, C.J.: Multi-objective and prioritized berth allocation in container ports. Annals of Operations Research 180(1), 63–103 (2010)
Cordeau, J.F., Laporte, G., Legato, P., Moccia, L.: Models and tabu search heuristics for the berth allocation problem. Transportation Science 39, 526–538 (2005)
Guan, Y., Xiao, W.Q., Cheung, R., Li, C.L.: A multiprocessor task scheduling model for berth allocation: heuristic and worst-case analysis. Operations Research Letters 30, 343–350 (2002)
Hamming, R.W.: Error detecting and error correcting codes. Bell System Technical Journal 26(2), 147–160 (1950)
Hansen, P., Oguz, C., Mladenovic, N.: Variable neighborhood search for minimum cost berth allocation. European Journal of Operational Research 191, 636–649 (2008)
Imai, A., Nishimura, E., Papadimitriou, S.: The dynamic berth allocation problem for a container port. Transportation Research Part B: Methodological 35, 401–417 (2001)
Imai, A., Nishimura, E., Papadimitriou, S.: Berth allocation with service priority. Transportation Research Part B: Methodological 37, 437–457 (2003)
Imai, A., Sun, X., Nishimura, E., Papadimitriou, S.: Berth allocation in a container port: using a continuous location space approach. Transportation Research Part B 39(3), 199–221 (2005)
Imai, A., Chen, H.C., Nishimura, E., Papadimitriou, S.: The simultaneous berth and quay crane allocation problem. Transportation Research Part E 44, 900–920 (2008)
Kim, K., Moon, K.: Berth scheduling by simulated annealing. Transportation Research B 37, 541–560 (2003)
Lee, D.H., Chen, J.H., Cao, J.X.: The continuous berth allocation problem: a greedy randomized adaptive search solution. Transportation Research Part E 46, 1017–1029 (2010)
Li, C.L., Cai, X., Lee, C.Y.: Scheduling with multiple-job-on-one-processor pattern. IIE Transactions 30, 433–445 (1998)
Lim, A.: The berth scheduling problem. Operations Research Letters 22, 105–110 (1998)
Mauri, G.R., Oliveira, A.C.M., Lorena, L.A.N.: A Hybrid Column Generation Approach for the Berth Allocation Problem. In: van Hemert, J., Cotta, C. (eds.) EvoCOP 2008. LNCS, vol. 4972, pp. 110–122. Springer, Heidelberg (2008)
Mauri, G.R., Andrade, L.N., Lorena, L.A.N.: A memetic algorithm for a continuous case of the berth allocation problem. In: ECTA 2011 - International Conference on Evolutionary Computation Theory and Applications, Paris, France (2011)
Monaco, M.F., Sammarra, M.: The berth allocation problem: a strong formulation solved by a lagrangean approach. Transportation Research Part B 41(2), 265–280 (2007)
Nishimura, E., Imai, A., Papadimitriou, S.: Berth allocation planning in the public berth system by genetic algorithms. European Journal of Operational Research 131, 282–292 (2001)
Oliveira, A.C.M., Lorena, L.A.N.: Hybrid evolutionary algorithms and clustering search. SCI, vol. 75, pp. 77–99 (2007)
Park, Y.M., Kim, K.H.: A scheduling method for Berth and Quay cranes. OR Spectrum 25, 1–23 (2003)
Seyedalizadeh Ganji, S.R., Babazadeh, A., Arabshahi, N.: Analysis of the continuous berth allocation problem in container ports using a genetic algorithm. Journal of Marine Science and Technology 15, 408–416 (2010)
Thurman, K.P.: Optimal ship berthing plans. Dissertation (Masters of Science in Operations Research) - Naval Postgraduate School, Monterey, California - EUA (1989)
UNCTAD: Review of maritime transport. United Nations conference on trade and development (2010)
Xu, D., Li, C.L., Leung, J.Y.: Berth allocation with time-dependent physical limitations on vessels. European Journal of Operational Research 216(1), 47–56 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
de Oliveira, R.M., Mauri, G.R., Lorena, L.A.N. (2012). Clustering Search Heuristic for Solving a Continuous Berth Allocation Problem. In: Hao, JK., Middendorf, M. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2012. Lecture Notes in Computer Science, vol 7245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29124-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-29124-1_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29123-4
Online ISBN: 978-3-642-29124-1
eBook Packages: Computer ScienceComputer Science (R0)