Abstract
This research is motivated by both the indispensable need for optimization in container terminals and the recent advances in swarm intelligence. In this paper, we try to address the Integrated Yard Truck Scheduling and Storage Allocation Problem (YTS-SAP), one of the major optimization problems in container port, which aims at minimizing the total delay for all containers. Bacterial colony optimization (BCO), a recently developed optimization algorithm that simulates some typical behaviors of E. coli bacteria, is introduced to address this NP-hard problem. In addition, we designed a mapping schema by which the particle position vector can be transferred to the scheduling solution. The performance of the BCO is investigated by an experiment conducted on different scale instances compared with PSO and GA. The results demonstrate the competitiveness of the proposed approach especially for large scale and complex problems.
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
Stahlbock, R., Voß, S.: Operations research at container terminals: a literature update. Or Spectrum 30(1), 1–52 (2008)
Bish, E.K., Thin-Yin, L., Chung-Lun, L., Ng, J.W.C., Simchi-Levi, D.: Analysis of a new vehicle scheduling and location problem. Naval Research Logistics 48(5), 363–385 (2001)
Wu, Y., Luo, J., Zhang, D., Dong, M.: An integrated programming model for storage management and vehicle scheduling at container terminals. Research in Transportation Economics 42(1), 13–27 (2013)
Lee, D.-H., Cao, J.X., Shi, Q., Chen, J.H.: A heuristic algorithm for yard truck schedul-ing and storage allocation problems. Transportation Research Part E: Logistics and Trans-portation Review 45(5), 810–820 (2009)
Sharif, O., Huynh, N.: Storage space allocation at marine container terminals using ant-based control. Expert Systems with Applications 40(6), 2323–2330 (2013)
Niu, B., Wang, H.: Bacterial Colony Optimization. Discrete Dynamics in Nature & Society, 1–28 (2012)
Niu, B., Wang, H., Duan, Q.Q., Li, L.: Biomimicry of Quorum Sensing Using Bacterial Lifecycle Model. BMC Bioinformatics 14(8), 1–13 (2013)
Fatih Tasgetiren, M., Liang, Y.-C., Sevkli, M., Gencyilmaz, G.: Particle swarm optimi-zation and differential evolution for the single machine total weighted tardiness problem. International Journal of Production Research 44(22), 4737–4754 (2006)
Shi, Y., Eberhart, R.: A Modified Particle Swarm Optimizer. In: Proceedings of 1998 IEEE International Conference on Evolutionary Computation Proceedings, pp. 69–73 (1998)
Sumathi, S., Hamsapriya, T., Surekha, P.: Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab. Springer Publishing Company, Incorporated (2008)
Niu, B., Wang, H., Wang, J.W., Tan, L.J.: Multi-objective Bacterial Foraging Optimization. Neurocomputing 116, 336–345 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Niu, B., Xie, T., Bi, Y., Liu, J. (2014). Bacterial Colony Optimization for Integrated Yard Truck Scheduling and Storage Allocation Problem. In: Huang, DS., Han, K., Gromiha, M. (eds) Intelligent Computing in Bioinformatics. ICIC 2014. Lecture Notes in Computer Science(), vol 8590. Springer, Cham. https://doi.org/10.1007/978-3-319-09330-7_50
Download citation
DOI: https://doi.org/10.1007/978-3-319-09330-7_50
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09329-1
Online ISBN: 978-3-319-09330-7
eBook Packages: Computer ScienceComputer Science (R0)