Abstract
Nowadays, Yard Truck Scheduling (YTS) and Storage Allocation Problem (SAP) are still two main problems in container terminal operations. Based on the current situation of using double trailer and practical constricts (e.g. container sorting storage, shore bridge and field bridge processing time), this paper proposes a realistic YTS-SAP model (YTSSAP). Additionally, a path interaction bacterial foraging optimization algorithm (PIBFO) is applied to solve the YTSSAP according to the differential tumbling label method and path interaction strategy. In the two strategies, each individual is given a label. If an individual has been employed as one individual’s interaction object, it will not be selected by the other bacteria. The population is easy to find the optimal solution using the path interaction strategy. The experiment results illustrate that PIBFO performs superior in dealing with the YTSSAP compared with coevolutionary structure-redesigned-based BFO (CSRBFO), comprehensive learning particle swarm optimizer (CLPSO) and genetic algorithm (GA). CLPSO obtains the worst results in terms of the performance and convergence rate when using it to solve the YTSSAP.
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Acknowledgment
This work is partially supported by The National Natural Science Foundation of China (Grants No. 61472257, 71701134), Natural Science Foundation of Guangdong Province (2016A030310074, 2017A030310427), The HD Video R & D Platform for Intelligent Analysis and Processing in Guangdong Engineering Technology Research Centre of Colleges and Universities (No.GCZX-A1409), The Postgraduate Innovation Development Fund Project of Shenzhen University (PIDFP-RW2018015).
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Liu, L., Xiao, L., Zuo, L., Liu, J., Yang, C. (2018). Application of BFO Based on Path Interaction in Yard Truck Scheduling and Storage Allocation Problem. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 952. Springer, Singapore. https://doi.org/10.1007/978-981-13-2829-9_22
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