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Decomposition-Based Memetic Algorithm for Multiobjective Capacitated Arc Routing Problem
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AI
DOI：10.1109/TEVC.2010.2051446.png)
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Abstract
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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 multiobjective CARP (MO-CARP). A new memetic algorithm (MA) called decomposition-based MA 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 multiobjective evolutionary optimization. Our experimental studies have shown that such combination outperforms significantly an off-the-shelf multiobjective evolutionary algorithm, namely nondominated sorting genetic algorithm II, and the state-of-the-art multiobjective algorithm for MO-CARP (LMOGA). Our work has also shown that a specifically designed multiobjective algorithm by combining its single-objective version and multiobjective features may lead to competitive multiobjective algorithms for multiobjective combinatorial optimization problems.
Keywords:
Capacitated arc routing problem (CARP)
local search
memetic algorithms (MA)
meta-heuristics
multiobjective optimization
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