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.
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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
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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
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