Diversity-Driven Selection of Multiple Crossover Operators for the Capacitated Arc Routing Problem

The Capacitated Arc Routing Problem (CARP) is a NP-Hard routing problem with strong connections with real world problems. In this work we aim to enhance the performance of MAENS, a state-of-the-art algorithm, through a self-adaptive scheme to choose the most suitable operator and a diversity-driven ranking operator. Experimental results on 181 problem instances show how these techniques can both improve the results of the current state-of-the-art algorithms and provide good directions to develop EAs with a more robust approximation ratio.

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