Artikel
Routing optimization of fourth party logistics with reliability constraints based on Messy GA
Purpose: The purpose of this paper is to choose a optimal routing in fourth party logistics (4PL) with the objective of transportation cost minimization under reliability level constraint. Design/methodology/approach: Reliability theory is applied to routing optimization problem. A mathematical model of the 4PL routing optimization problem with reliability constraints is built, which aims to find a route at the minimum cost. Due to the 4PL routing problem is NP-hard, two algorithms are designed: Messy Genetic Algorithm (Messy GA) and Enumeration Algorithm (EA). Findings: Through the model and algorithm, 4PL company can obtain the optimal solution quickly and effectively, according to customer's reliability requirements. Practical implications : We give an example for test the effectiveness of the method and the algorithm. Originality/value: In this paper, we put objective factors that cause disturbances of transportation time into consideration, and reliability theory is applied to 4PL routing optimization problem. A Messy GA with double arrays encoding method is designed to solve the problem.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 7 ; Year: 2014 ; Issue: 5 ; Pages: 1097-1111 ; Barcelona: OmniaScience
- Classification
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Management
- Subject
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fourth party logistics
reliability constraints
routing optimization
Messy Genetic Algorithm
Enumeration Algorithm
- Event
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Geistige Schöpfung
- (who)
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Li, Jia
Yanqiu, Liu
Zhongjun, Hu
- Event
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Veröffentlichung
- (who)
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OmniaScience
- (where)
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Barcelona
- (when)
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2014
- DOI
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doi:10.3926/jiem.1126
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Li, Jia
- Yanqiu, Liu
- Zhongjun, Hu
- OmniaScience
Time of origin
- 2014
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