Paper Info
Title
Model and algorithm for 4PLRP with uncertain delivery time.
Abstract
To address the challenge of logistics routing decision under uncertain environment, this paper studies a fourth party logistics routing problem (4PLRP) with uncertain delivery time (4PLRPU). A novel 4PLRPU model based on uncertainty theory is proposed by describing the delivery time of a third party logistics (3PL) provider as an uncertain variable. After that, the model is transformed into an equivalent deterministic model, and several improved genetic algorithms are designed to get solutions. To handle the problem of infeasible solutions in the proposed 4PLRPU, an improved node-based genetic algorithm (INGA) and an improved distance-based genetic algorithm (IDGA) are developed to reduce the computing time required to repair infeasible solutions, and an improved genetic algorithm based on the simple graph and Dijkstra algorithm (SDGA) is proposed to avoid the generation of infeasible solutions. Numerical experiments are conducted to investigate the performance of the proposed algorithms and verify the effectiveness of the proposed 4PLRPU model. The results show that INGA and SDGA are more effective than the standard genetic algorithm and IDGA at solving large-scale problems. Additionally, compared with the expected value model, the 4PLRPU model is more robust.
Year
DOI
Venue
2016
10.1016/j.ins.2015.10.030
Information Sciences
Keywords
Field
DocType
Fourth party logistics routing problem,Uncertainty theory,Multi-graph,Intelligent algorithm,Shortest path problem
Mathematical optimization,Shortest path problem,Computer science,Algorithm,Third party,Uncertain variable,Expected value,Deterministic system,Genetic algorithm,Dijkstra's algorithm,Uncertainty theory
Journal
Volume
Issue
ISSN
330
C
0020-0255
Citations 
PageRank 
References 
4
0.43
27
Authors
6
Name
Order
Citations
PageRank
Min Huang142371.49
Liang Ren240.43
Loo Hay Lee3115993.96
Xingwei Wang41025154.16
Hanbin Kuang5313.45
Haibo Shi6137.57