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.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 7 ; Year: 2014 ; Issue: 5 ; Pages: 1097-1111 ; Barcelona: OmniaScience
- Klassifikation
-
Management
- Thema
-
fourth party logistics
reliability constraints
routing optimization
Messy Genetic Algorithm
Enumeration Algorithm
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Li, Jia
Yanqiu, Liu
Zhongjun, Hu
- Ereignis
-
Veröffentlichung
- (wer)
-
OmniaScience
- (wo)
-
Barcelona
- (wann)
-
2014
- DOI
-
doi:10.3926/jiem.1126
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Li, Jia
- Yanqiu, Liu
- Zhongjun, Hu
- OmniaScience
Entstanden
- 2014
Ähnliche Objekte (12)
Dynamic financial and monetary security risk assessment based on information service security assessment model and blockchain
Grounded theory-based model of the influence of digital communication on handicraft intangible cultural heritage
Kano-QFD-based analysis of the influence of user experience on the design of handicraft intangible cultural heritage apps
Diagnostic and prognostic values of pyroptosis-related genes for the hepatocellular carcinoma
Analysis of decarbonization path in New York state and forecasting carbon emissions using different machine learning algorithms
EDS1 modules as two-tiered receptor complexes for TIR-catalyzed signaling molecules to activate plant immunity
Local boundedness and Harnack inequality for an inverse variational inequality problem with double nonlinear parabolic operator in finance
Peripheral multilingual scholars confronting epistemic exclusion in global academic knowledge production: a positive case study
Impulse oscillometry system and pulmonary function test assessment of the impact of tumor location, staging, and pathological type on lung function in primary lung cancer
Explainable machine learning by SEE-Net: closing the gap between interpretable models and DNNs
Jump factor models in large cross-sections
Fixed-k inference for volatility
Dynamic financial and monetary security risk assessment based on information service security assessment model and blockchain
Grounded theory-based model of the influence of digital communication on handicraft intangible cultural heritage
Kano-QFD-based analysis of the influence of user experience on the design of handicraft intangible cultural heritage apps
Diagnostic and prognostic values of pyroptosis-related genes for the hepatocellular carcinoma
Analysis of decarbonization path in New York state and forecasting carbon emissions using different machine learning algorithms
EDS1 modules as two-tiered receptor complexes for TIR-catalyzed signaling molecules to activate plant immunity
Local boundedness and Harnack inequality for an inverse variational inequality problem with double nonlinear parabolic operator in finance
Peripheral multilingual scholars confronting epistemic exclusion in global academic knowledge production: a positive case study
Impulse oscillometry system and pulmonary function test assessment of the impact of tumor location, staging, and pathological type on lung function in primary lung cancer
Explainable machine learning by SEE-Net: closing the gap between interpretable models and DNNs
Jump factor models in large cross-sections
Fixed-k inference for volatility
Dynamic financial and monetary security risk assessment based on information service security assessment model and blockchain
Grounded theory-based model of the influence of digital communication on handicraft intangible cultural heritage
Kano-QFD-based analysis of the influence of user experience on the design of handicraft intangible cultural heritage apps
Diagnostic and prognostic values of pyroptosis-related genes for the hepatocellular carcinoma
Analysis of decarbonization path in New York state and forecasting carbon emissions using different machine learning algorithms
EDS1 modules as two-tiered receptor complexes for TIR-catalyzed signaling molecules to activate plant immunity
Local boundedness and Harnack inequality for an inverse variational inequality problem with double nonlinear parabolic operator in finance
Peripheral multilingual scholars confronting epistemic exclusion in global academic knowledge production: a positive case study
Impulse oscillometry system and pulmonary function test assessment of the impact of tumor location, staging, and pathological type on lung function in primary lung cancer
Explainable machine learning by SEE-Net: closing the gap between interpretable models and DNNs
Jump factor models in large cross-sections