Please use this identifier to cite or link to this item: https://doi.org/10.1016/S1007-0214(08)70151-2
DC FieldValue
dc.titleA Decision Support Method for Truck Scheduling and Storage Allocation Problem at Container
dc.contributor.authorCao, J.
dc.contributor.authorShi, Q.
dc.contributor.authorLee, D.-H.
dc.date.accessioned2014-06-16T09:26:16Z
dc.date.available2014-06-16T09:26:16Z
dc.date.issued2008-10
dc.identifier.citationCao, J.,Shi, Q.,Lee, D.-H. (2008-10). A Decision Support Method for Truck Scheduling and Storage Allocation Problem at Container. Tsinghua Science and Technology 13 (SUPPL. 1) : 211-216. ScholarBank@NUS Repository. <a href="https://doi.org/10.1016/S1007-0214(08)70151-2" target="_blank">https://doi.org/10.1016/S1007-0214(08)70151-2</a>
dc.identifier.issn10070214
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/54055
dc.description.abstractTruck scheduling and storage allocation, as two separate subproblems in port operations, have been deeply studied in past decades. However, from the operational point of view, they are highly interdependent. Storage allocation for import containers has to balance the travel time and queuing time of each container in yard. This paper proposed an integer programming model handling these two problems as a whole. The objective of this model is to reduce congestion and waiting time of container trucks in the terminal so as to decrease the makespan of discharging containers. Due to the inherent complexity of the problem, a genetic algorithm and a greedy heuristic algorithm are designed to attain near optimal solutions. It shows that the heuristic algorithm can achieve the optimal solution for small-scale problems. The solutions of small-and large-scale problems obtained from the heuristic algorithm are better than those from the genetic algorithm. © 2008 Tsinghua University Press.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S1007-0214(08)70151-2
dc.sourceScopus
dc.subjectcontainer terminal
dc.subjectgenetic algorithms
dc.subjectheuristic algorithm
dc.subjectvehicle scheduling
dc.typeArticle
dc.contributor.departmentCIVIL ENGINEERING
dc.description.doi10.1016/S1007-0214(08)70151-2
dc.description.sourcetitleTsinghua Science and Technology
dc.description.volume13
dc.description.issueSUPPL. 1
dc.description.page211-216
dc.description.codenTSTEF
dc.identifier.isiutNOT_IN_WOS
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