Decomposition-Based Memetic Algorithm for Multiobjective Capacitated Arc Routing Problem

• Published in: IEEE transactions on evolutionary computation Vol. 15; no. 2; pp. 151 - 165
• Main Authors: Mei, Yi, Tang, Ke, Yao, Xin
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.04.2011; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithmics. Computability. Computer arithmetics; Algorithms; Applied sciences; Capacitated arc routing problem (CARP); Carp; Combinatorial analysis; Computer science; control theory; systems; Decomposition; Diversity reception; Evolutionary; Evolutionary algorithms; Exact sciences and technology; Flows in networks. Combinatorial problems; Genetic algorithms; local search; Logistics; Mathematical programming; memetic algorithms (MA); Memetics; meta-heuristics; Molybdenum; multiobjective optimization; Operational research and scientific management; Operational research. Management science; Optimization; Route optimization; Routing; Salting; Sorting; Studies; Theoretical computing; Vehicles; Local search; Fleet; Fleet management; Combinatorial problem; Evolutionary algorithm; Multiobjective programming; Routing; Combinatorial optimization; Competitive algorithms; Capacitated arc routing problem CARP; multiobjective optimization; Memetic algorithm; Capacitated arc routing problem (CARP); Neighborhood search; Genetic algorithm; memetic algorithms (MA); Heuristic method; Capacity constraint; Metamodel; meta-heuristics; Logistics
• ISSN: 1089-778X; 1941-0026
• DOI: 10.1109/TEVC.2010.2051446

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.