Decomposing Large-Scale Capacitated Arc Routing Problems using a random route grouping method

Yi Mei, Xiaodong Li, Xin Yao

Abstract: 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.