Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode

Joint Authors

Wang, Li
Zhu, Xiaoning

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-11-04

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Biology

Abstract EN

Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency.

In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks.

An ant colony optimization is proposed to obtain near optimal solutions.

Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm.

The results show that the proposed method is effective in reducing the idle load time of RMGC.

American Psychological Association (APA)

Wang, Li& Zhu, Xiaoning. 2014. Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1016740

Modern Language Association (MLA)

Wang, Li& Zhu, Xiaoning. Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1016740

American Medical Association (AMA)

Wang, Li& Zhu, Xiaoning. Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1016740

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1016740