Path optimization based on hybrid intelligent algorithm of emergency logistics

Yanbing Ju; Lingyun Sun; Aihua Wang

doi:10.1109/ICNC.2010.5583606

Path optimization based on hybrid intelligent algorithm of emergency logistics

Yanbing Ju^*
, Lingyun Sun
, Aihua Wang

^*Corresponding author for this work

School of Management

Beijing Institute of Technology
Peking University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Path optimization problem is an important component of Emergency Logistics. According to the emergency incidents occurring in Emergency Logistics, We build an uncertain programming model, which is based on the shortest travel time as the objective function, and make the model closer to reality. The model use the traffic time as fuzzy variable, the demand quantity of disaster location as random variable, and in consideration of vehicles required to service within a specified time window, otherwise it will cause more losses. A hybrid algorithm is proposed to solve the model. Results show the effectiveness and feasibility of the model and algorithm.

Original language	English
Title of host publication	Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
Publisher	IEEE Computer Society
Pages	1285-1289
Number of pages	5
ISBN (Print)	9781424459612
DOIs	https://doi.org/10.1109/ICNC.2010.5583606
Publication status	Published - 2010

Publication series

Name	Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
Volume	3

Keywords

Emergency logistics
Hybrid intelligent algorithm
Path optimization
Uncertain programming

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10.1109/ICNC.2010.5583606

Cite this

Ju, Y., Sun, L., & Wang, A. (2010). Path optimization based on hybrid intelligent algorithm of emergency logistics. In Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010 (pp. 1285-1289). Article 5583606 (Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010; Vol. 3). IEEE Computer Society. https://doi.org/10.1109/ICNC.2010.5583606

@inproceedings{9d9e4745fe5e46f7a0568e430d3c0446,

title = "Path optimization based on hybrid intelligent algorithm of emergency logistics",

abstract = "Path optimization problem is an important component of Emergency Logistics. According to the emergency incidents occurring in Emergency Logistics, We build an uncertain programming model, which is based on the shortest travel time as the objective function, and make the model closer to reality. The model use the traffic time as fuzzy variable, the demand quantity of disaster location as random variable, and in consideration of vehicles required to service within a specified time window, otherwise it will cause more losses. A hybrid algorithm is proposed to solve the model. Results show the effectiveness and feasibility of the model and algorithm.",

keywords = "Emergency logistics, Hybrid intelligent algorithm, Path optimization, Uncertain programming",

author = "Yanbing Ju and Lingyun Sun and Aihua Wang",

year = "2010",

doi = "10.1109/ICNC.2010.5583606",

language = "English",

isbn = "9781424459612",

series = "Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010",

publisher = "IEEE Computer Society",

pages = "1285--1289",

booktitle = "Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010",

address = "United States",

}

Ju, Y, Sun, L & Wang, A 2010, Path optimization based on hybrid intelligent algorithm of emergency logistics. in Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010., 5583606, Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010, vol. 3, IEEE Computer Society, pp. 1285-1289. https://doi.org/10.1109/ICNC.2010.5583606

Path optimization based on hybrid intelligent algorithm of emergency logistics. / Ju, Yanbing; Sun, Lingyun; Wang, Aihua.
Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010. IEEE Computer Society, 2010. p. 1285-1289 5583606 (Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ju, Yanbing

AU - Sun, Lingyun

AU - Wang, Aihua

PY - 2010

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N2 - Path optimization problem is an important component of Emergency Logistics. According to the emergency incidents occurring in Emergency Logistics, We build an uncertain programming model, which is based on the shortest travel time as the objective function, and make the model closer to reality. The model use the traffic time as fuzzy variable, the demand quantity of disaster location as random variable, and in consideration of vehicles required to service within a specified time window, otherwise it will cause more losses. A hybrid algorithm is proposed to solve the model. Results show the effectiveness and feasibility of the model and algorithm.

AB - Path optimization problem is an important component of Emergency Logistics. According to the emergency incidents occurring in Emergency Logistics, We build an uncertain programming model, which is based on the shortest travel time as the objective function, and make the model closer to reality. The model use the traffic time as fuzzy variable, the demand quantity of disaster location as random variable, and in consideration of vehicles required to service within a specified time window, otherwise it will cause more losses. A hybrid algorithm is proposed to solve the model. Results show the effectiveness and feasibility of the model and algorithm.

KW - Emergency logistics

KW - Hybrid intelligent algorithm

KW - Path optimization

KW - Uncertain programming

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U2 - 10.1109/ICNC.2010.5583606

DO - 10.1109/ICNC.2010.5583606

M3 - Conference contribution

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T3 - Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010

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BT - Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010

PB - IEEE Computer Society

ER -

Path optimization based on hybrid intelligent algorithm of emergency logistics

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