Memetic Algorithm With Extended Neighborhood Search for Capacitated Arc Routing Problems

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The capacitated arc routing problem (CARP) has attracted much attention during the last few years due to its wide applications in real life. Since CARP is NP-hard and exact methods are only applicable to small instances, heuristic and metaheuristic methods are widely adopted when solving CARP. In this paper, we propose a memetic algorithm, namely memetic algorithm with extended neighborhood search (MAENS), for CARP. MAENS is distinct from existing approaches in the utilization of a novel local search operator, namely Merge-Split (MS). The MS operator is capable of searching using large step sizes, and thus has the potential to search the solution space more efficiently and is less likely to be trapped in local optima. Experimental results show that MAENS is superior to a number of state-of-the-art algorithms, and the advanced performance of MAENS is mainly due to the MS operator. The application of the MS operator is not limited to MAENS. It can be easily generalized to other approaches.


Original languageEnglish
Pages (from-to)1151-1166
Number of pages16
JournalIEEE Transactions on Evolutionary Computation
Issue number5
Publication statusPublished - 1 Oct 2009


  • memetic algorithm, Capacitated arc routing problem (CARP), evolutionary optimization, metaheuristic search, local search