An Improved Decomposition-Based Memetic Algorithm for Multi-Objective Capacitated Arc Routing Problem

The Capacitated Arc Routing Problem (CARP) is a challenging combinatorial optimization problem with many real-world applications, e.g., salting route optimization and fleet management. There have been many attempts at solving CARP using heuristic and meta-heuristic approaches, including evolutionary algorithms. However, almost all such attempts formulate CARP as a single-objective problem although it usually has more than one objective, especially considering its real-world applications. This paper studies multi-objective CARP (MO-CARP). A new memetic algorithm called Decomposition-based Memetic Algorithm with Extended Neighborhood Search (D-MAENS) is proposed. The new algorithm combines the advanced features from both the MAENS approach for single-objective CARP and multi-objective evolutionary optimization. Our experimental studies have shown that such combination outperforms significantly an off-the-shelf multi-objective evolutionary algorithm (NSGAII) and the state-of-the-art multi-objective algorithm for MO-CARP (LMOGA). Our work has also shown that a specifically designed multi-objective algorithm by combining its single-objective version and multi-objective features may lead to competitive multi-objective algorithms for multi-objective combinatorial optimization problems.