Computers and Operations Research
Routing winter gritting vehicles
CO89 Selected papers of the conference on Combinatorial Optimization
A new evolutionary approach to cutting stock problems with and without contiguity
Computers and Operations Research
A cutting plane algorithm for the capacitated arc routing problem
Computers and Operations Research
A Tabu Search Heuristic for the Capacitated Arc Routing Problem
Operations Research
A Variable Neighborhood Descent Algorithm for the Undirected Capacitated Arc Routing Problem
Transportation Science
Memetic algorithms for parallel code optimization
International Journal of Parallel Programming
A deterministic tabu search algorithm for the capacitated arc routing problem
Computers and Operations Research
A global repair operator for capacitated arc routing problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Solving capacitated arc routing problems using a transformation to the CVRP
Computers and Operations Research
Robust route optimization for gritting/salting trucks: a CERCIA experience
IEEE Computational Intelligence Magazine
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
A study of the Lamarckian evolution of recurrent neural networks
IEEE Transactions on Evolutionary Computation
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
Evolutionary programming using mutations based on the Levy probability distribution
IEEE Transactions on Evolutionary Computation
Meta-Lamarckian learning in memetic algorithms
IEEE Transactions on Evolutionary Computation
Systematic integration of parameterized local search into evolutionary algorithms
IEEE Transactions on Evolutionary Computation
A Memetic Algorithm for VLSI Floorplanning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Towards a memetic feature selection paradigm
IEEE Computational Intelligence Magazine
An evolutionary approach to the multidepot capacitated arc routing problem
IEEE Transactions on Evolutionary Computation
An optimization-based heuristic for the Multi-objective Undirected Capacitated Arc Routing Problem
Computers and Operations Research
SEA'10 Proceedings of the 9th international conference on Experimental Algorithms
A developmental solution to (dynamic) capacitated arc routing problems using genetic programming
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Using computational intelligence for large scale air route networks design
Applied Soft Computing
Unpacking and understanding evolutionary algorithms
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
Memetic algorithms for de novo motif-finding in biomedical sequences
Artificial Intelligence in Medicine
Efficient solution of capacitated arc routing problems with a limited computational budget
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Improved bounds for large scale capacitated arc routing problem
Computers and Operations Research
Power law-based local search in differential evolution
International Journal of Computational Intelligence Studies
The double layer optimization problem to express logistics systems and its heuristic algorithm
Expert Systems with Applications: An International Journal
Natural Computing: an international journal
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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.