An Improved Path Optimum Algorithm for Container Relocation Problems in Port Terminals Worldwide

• Published in: Journal of coastal research 2018-05, Vol.34 (3), p.752-765
• Main Authors: Zheng, Sisi, Wang, Aihu, Mehmood, Fahad, Mohmand, Yasir Tariq
• Format: Article
• Language: English
• Subjects: Algorithms; Automation; Business administration; Coasts; Coefficients; Competitive advantage; Container terminals; Containers; Departure time; Efficiency; Extractive sequence; Gantry cranes; general expression; Goal programming; Heuristic; heuristic rules; Heuristics; Humanities and Social Sciences; Hunting; Industrial engineering; Integer programming; least number of relocations; Logistics; Mathematical models; Mathematical problems; Modeling; Operations research; Ports; Reliability analysis; Relocation; Resource scheduling; Robustness (mathematics); Run time (computers); Sensitivity analysis; Solution space; Solutions; Storage; Storage containers; TECHNICAL COMMUNICATIONS; two-level goal programming model; Water hardness
• ISSN: 0749-0208; 1551-5036
• DOI: 10.2112/JCOASTRES-D-17-00056.1

Zheng, S.; Wang, A.; Mehmood, F., and Mohmand, Y.T., 2018. An improved path optimum algorithm for container relocation problems in port terminals worldwide. The container relocation problem (CRP) for ports worldwide has been a highly significant research topic because of its contribution to the improvement of yard-running efficiency. It can be defined as a sequence that allows each container to be extracted with the least number of relocations when identical containers in a cluster have been stacked in a block. This study differs from previous research mainly in five aspects: (1) a two-level goal programming model for CRP is presented that can help in understanding of this problem and provide a solid theoretical ground for this research; (2) because of the NP time hardness of the CRP, heuristic rules are proposed to reduce hunting space by the way of dividing solution space; (3) an improved path optimum algorithm (I-POA) is proposed to reduce unfeasible solutions and find a high-quality solution for any three-dimensional case in a shorter running time; (4) the numerical experiments show that the algorithm proposed in this research achieves better performance than similar algorithms because of its higher levels of efficiency and more robust property; and (5) a general expression for the utilization level of the storage area and the number of relocations is proposed to check the reliability of the result by conducting a sensitivity analysis. Based on this research, the following conclusion can be obtained: I-POA possesses significant practical value in the improvement of intelligent resource scheduling standards of coastal container ports worldwide.