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Title: Minimization of delay and travel time of yard trucks in container terminals using an improved GA with guidance search
Authors: Wang, ZX 
Chan, FTS 
Chung, SH 
Niu, B
Issue Date: 2015
Publisher: Hindawi Publishing Corporation
Source: Mathematical problems in engineering, 2015, 710565 How to cite?
Journal: Mathematical problems in engineering 
Abstract: Yard truck scheduling and storage allocation problems (YTS-SAP) are two important issues that influence the efficiency of a container terminal. These two problems aim to determine the routing of trucks and proper storage locations for discharging containers from incoming vessels. This paper integrates YTS and SAP as a whole and tries to minimize the weighted summation of total delay and total yard trucks travel time. A genetic algorithm (GA) is proposed to deal with the problem. In the proposed GA, guidance mutation approach and exhaustive heuristic for local searching are used in order to force the GA to converge faster and be steadier. To test the performance of the proposed GA, both small scale and large scale cases are studied. The results of these cases are compared with CPLEX for the small scale cases. Since this problem is an NP-hard problem, which CPLEX cannot solve, a simple GA is studied for comparison in large scale cases. The comparison demonstrates that the proposed GA can obtain near optimal solutions in much shorter computational time for small scale cases. In addition, the proposed GA can obtain better results than other methods in reasonable time for large scale cases.
ISSN: 1024-123X
EISSN: 1563-5147
DOI: 10.1155/2015/710565
Rights: Copyright © 2015 Z. X. Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following article: Wang, Z. X., Chan, F. T., Chung, S. H., & Niu, B. (2015). Minimization of delay and travel time of yard trucks in container terminals using an improved GA with guidance search. Mathematical Problems in Engineering, 2015, is available at https//
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