TY - GEN
T1 - Decomposing large-scale capacitated arc routing problems using a random route grouping method
AU - MEI, Yi
AU - LI, Xiaodong
AU - YAO, Xin
PY - 2013/6
Y1 - 2013/6
N2 - In this paper, a simple but effective Random Route Grouping (RRG) scheme is developed to decompose the Large-Scale 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. © 2013 IEEE.
AB - In this paper, a simple but effective Random Route Grouping (RRG) scheme is developed to decompose the Large-Scale 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. © 2013 IEEE.
UR - http://www.scopus.com/inward/record.url?scp=84881567888&partnerID=8YFLogxK
U2 - 10.1109/CEC.2013.6557678
DO - 10.1109/CEC.2013.6557678
M3 - Conference paper (refereed)
SN - 9781479904549
SP - 1013
EP - 1020
BT - 2013 IEEE Congress on Evolutionary Computation, CEC 2013
ER -