DocumentCode :
2127253
Title :
A Strategy for Yard Crane Scheduling Based on Hybrid Parallel Genetic Algorithm
Author :
He, Junliang ; Chang, Daofang ; Mi, Weijian ; Yan, Wei
Author_Institution :
Container Supply Chain Technol. Eng. Res. Center, Minist. of Educ., Shanghai
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
678
Lastpage :
683
Abstract :
Container terminals play a crucial role in container transportation, including shipping and land transportation. In particular, container yard management, which involves diverse operational services, significantly affects the operational efficiency of the entire container terminal. However, there is a major omission in existing work, viz., it is imperative to attain an effective workload scheduling to support the dynamic scheduling of yard cranes. Based on these understandings, the study aims at postulating a novel strategy in terms of yard crane scheduling. In this manner, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-hard problem regarding the yard crane scheduling, a hybrid algorithm which employs heuristic rule and parallel genetic algorithm, is then employed. Finally, a case simulation study has been used for system illustration, and then verifies the validity and usefulness of the model and the algorithm.
Keywords :
computational complexity; containers; dynamic scheduling; genetic algorithms; parallel algorithms; transportation; NP-hard problem; container terminal; container transportation; container yard management; heuristic rule; hybrid parallel genetic algorithm; land transportation; objective programming; rolling-horizon approach; shipping; yard crane dynamic scheduling; Containers; Costs; Cranes; Dynamic programming; Dynamic scheduling; Genetic algorithms; Loading; NP-hard problem; Optimal scheduling; Scheduling algorithm; container terminals; hybrid parallel genetic algorithm; rolling-horizon approach; simulation; yard crane scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
Type :
conf
DOI :
10.1109/KAM.2008.81
Filename :
4732914
Link To Document :
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