Chapter
Jan 13, 2020
Sixth International Conference on Transportation Engineering

Optimization of Loading Scheme on Railway Dangerous Goods

Publication: ICTE 2019

ABSTRACT

Railway dangerous goods storage yard has many characteristics, such as large storage types, large storage capacity. The optimization of railway dangerous goods loading scheme can be regarded as an optimization problem related to the operation route. According to the characteristics of dangerous goods storage, this paper establishes a mathematical model of dangerous goods loading scheme, and uses genetic algorithm to solve it. The optimal goods allocation, loading scheme, and the minimum operating time are obtained.

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ACKNOWLEDGEMENT

The paper is partially supported by the National Key Research and Development Program of China (GRANT No. 2016YFC0802209).

REFERENCES

LI, Jing (2018). “Optimization Model and Application Research of P Company's Cargo Storage Location.” Southwest Petroleum University.
LIU, Zenghui (2018). “Research on Optimization of Storage Location of Container Based on Genetic Simulated Annealing Algorithm.” Modern Industrial Economy and Informationization, 2018,8(17): 23-24.
LIU, Weiwei (2018). “Study on the warehousing slotting optimization based on improved adaptive genetic algorithm.” Computer Era, 2018(08): 57-60.
MA, Jianwen, CAI, Boni, LI, Chen (2018). “Relationship between fire-fighting facilities and general layout in dangerous goods logistics par.” Port & Waterway Engineering, 2018(06): 302-306.
WANG, Lei (2018). “Optimization research on warehouse management of hazardous goods under uncertainty.” Southwest Jiaotong University.
XIA, Xiankang (2015). “Optimization of picking route for elevated warehouse based on genetic algorithm.” Railway Freight Transport, 2015,33(09): 39-42.
ZHAI, haitao (2018). “Research on Optimization of Freight Position in SR Automated Warehouse.” Changchun University Of Technology.

Information & Authors

Information

Published In

Go to ICTE 2019
ICTE 2019
Pages: 470 - 476
Editors: Xiaobo Liu, Ph.D., Southwest Jiaotong University, Qiyuan Peng, Ph.D., Southwest Jiaotong University, and Kelvin C. P. Wang, Ph.D., Oklahoma State University
ISBN (Online): 978-0-7844-8274-2

History

Published online: Jan 13, 2020

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Authors

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Xiang Huang [email protected]
Southwest Jiaotong Univ., Chengdu. E-mail: [email protected]
Ruifang Mou [email protected]
Southwest Jiaotong Univ., Chengdu (corresponding author). E-mail: [email protected]

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