A hybrid parallel genetic algorithm for yard crane scheduling

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a...

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Bibliographic Details
Published in:Transportation research. Part E, Logistics and transportation review Logistics and transportation review, 2010, Vol.46 (1), p.136-155
Main Authors: He, Junliang, Chang, Daofang, Mi, Weijian, Yan, Wei
Format: Article
Language:English
Subjects:
Cranes & hoists
Dynamic programming
Genetic algorithms
Heuristic
Heuristic rules
Mathematical models
Objective programming
Parallel genetic algorithm
Scheduling
Scheduling algorithms
Simulation model
Studies
Yard crane scheduling
Yard crane scheduling Objective programming Heuristic rules Parallel genetic algorithm Simulation model
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Summary:This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently.
ISSN:1366-5545
1878-5794
DOI:10.1016/j.tre.2009.07.002