Paper Info
Title
Two-echelon location-routing optimization with time windows based on customer clustering.
Abstract
•A two-echelon location-routing problem is optimized based on customer partitioning.•A mathematical model is proposed to minimize cost and maximize service reliability.•Customers demand uncertainty is assumed and estimated during optimization.•A modified NSGA-II method and a validity function are designed to obtain solutions.•Computational results reveal that M-NSGA-II outperforms MOGA and MOPSO algorithms.
Year
DOI
Venue
2018
10.1016/j.eswa.2018.03.018
Expert Systems with Applications
Keywords
Field
DocType
Location routing optimization with time windows,Periodic demand forecasting,Customer clustering,Validity measurement function,Non-dominated Sorting Genetic Algorithm-II (NSGA-II)
Customer relationship management,Particle swarm optimization,Data mining,Genetic operator,Vehicle routing problem,Customer satisfaction,Crossover,Computer science,Cluster analysis,Genetic algorithm
Journal
Volume
ISSN
Citations 
104
0957-4174
2
PageRank 
References 
Authors
0.36
20
6
Name
Order
Citations
PageRank
Yinhai Wang129239.37
Yinhai Wang229239.37
Kevin Assogba321.03
Yong Liu4323.77
Xiaolei Ma520315.59
Maozeng Xu6365.92