The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization

Joint Authors

Lu, Fuqiang
Feng, Wenjing
Gao, Mengying
Bi, Hualing
Wang, Suxin

Source

Journal of Advanced Transportation

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-10-15

Country of Publication

Egypt

No. of Pages

15

Main Subjects

Civil Engineering

Abstract EN

The fourth-party logistics routing problem (4PLRP) is an important issue in the operation of fourth-party logistics (4PL).

In this paper, the study of fourth-party logistics (4PL) path optimization considers that more third-party logistics (3PL) undertake transportation tasks.

Under the condition that the 3PL transportation time, transportation cost, node transit time, and transit cost are uncertain, 4PL provides customers with a set of transportation solutions to transport transportation tasks from the initial node to the destination node according to the customer’s risk aversion preference.

The transportation scheme not only meets the customer’s time and cost requirements but also meets the carrying capacity and reputation constraints of 3PL.

Between the two nodes, one or more 3PLs will undertake the transportation task.

The customer’s risk preference will be measured by the ratio utility theory (RUT).

An ant colony system-improved grey wolf optimization (ACS-IGWO) is designed to solve the model, and the grey wolf optimization (GWO) is improved by the convergence factor and the proportional weight.

Problem analysis is conducted through simulation experiments.

American Psychological Association (APA)

Lu, Fuqiang& Feng, Wenjing& Gao, Mengying& Bi, Hualing& Wang, Suxin. 2020. The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1176337

Modern Language Association (MLA)

Lu, Fuqiang…[et al.]. The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization. Journal of Advanced Transportation No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1176337

American Medical Association (AMA)

Lu, Fuqiang& Feng, Wenjing& Gao, Mengying& Bi, Hualing& Wang, Suxin. The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1176337

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1176337