Title :
A Genetic Clustering-Based TCNN Algorithm for Capacity Vehicle Routing Problem
Author :
Sun, Huali ; Xie, Jianying ; Xue, Yaofeng
Author_Institution :
Dept. of Autom., Shanghai Jiaotong Univ.
Abstract :
A novel genetic clustering-based transiently chaotic neural network (GCTCNN) algorithm for capacity vehicle routing problem (CVRP) is proposed. CVRP can be partitioned into two kinds of decisions: the selection of vehicles among the available vehicles and the routing of the selected fleet. Using the clustering algorithm the customers are grouped into clusters and each cluster is served by one vehicle. Then transiently chaotic neural network solves the routes to optimality. Computation on benchmark problems and comparison with other known algorithm show that the proposed algorithm produces excellent solutions in short computing times
Keywords :
computational complexity; neural nets; pattern clustering; transportation; capacity vehicle routing problem; clustering algorithm; genetic clustering-based transiently chaotic neural network; Chaos; Clustering algorithms; Costs; Genetics; Logistics; Neural networks; Partitioning algorithms; Routing; Sun; Vehicles;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614611
