DocumentCode :
617928
Title :
Decomposing Large-Scale Capacitated Arc Routing Problems using a random route grouping method
Author :
Yi Mei ; Xiaodong Li ; Xin Yao
Author_Institution :
Sch. of Comput. Sci. & Inf. Technol., RMIT Univ., Melbourne, VIC, Australia
fYear :
2013
fDate :
20-23 June 2013
Firstpage :
1013
Lastpage :
1020
Abstract :
In this paper, a simple but effective Random Route Grouping (RRG) scheme is developed to decompose the LargeScale Capacitated Arc Routing Problem (LSCARP). A theoretical analysis is given to show that the decomposition is guaranteed to be improved by RRG along with the improvement of the best-sofar solution during the search process. Then, RRG is combined with a cooperative co-evolution model to solve LSCARP. The experimental results on the EGL-G LSCARP set showed that given the same computational budget, the proposed approach obtained much better results than its counterpart without using decomposition.
Keywords :
evolutionary computation; random processes; search problems; set theory; vehicle routing; EGL-G LSCARP set; RRG scheme; computational budget; cooperative co-evolution model; large-scale capacitated arc routing problem decomposition; random route grouping method; search process; Computer science; Educational institutions; Evolutionary computation; Optimization; Routing; Vectors; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
Type :
conf
DOI :
10.1109/CEC.2013.6557678
Filename :
6557678
Link To Document :
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