A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Augment-insert algorithms for the capacitated arc routing problem
Computers and Operations Research
Routing winter gritting vehicles
CO89 Selected papers of the conference on Combinatorial Optimization
A tabu scatter search metaheuristic for the arc routing problem
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
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
Solving capacitated arc routing problems using a transformation to the CVRP
Computers and Operations Research
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
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
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Capacitated Arc Routing Problem (CARP) has attracted much interest because of its wide applications in the real world. Recently, a memetic algorithm proposed by Lacomme et al. (LMA) has been demonstrated to be a competitive approach to CARP. The crossover operation of LMA is carried out based on an implicit representation scheme, while it conducts local search on the basis of an explicit representation scheme. Hence, the search process of LMA involves frequent switch between the spaces defined by the two representation schemes. However, a good solution in one space is not necessarily good in the other. In this paper, we show that the local search process of LMA might be ineffective due to such reason, and suggest adopting a more careful way to coordinate the local search. As a result, two new local search methods are proposed, which resulted in two improved LMA (ILMA) algorithms. Experimental results on benchmark instances of CARP showed that the ILMA significantly outperformed LMA in terms of solution quality, and sometimes even in terms of computational time. Furthermore, ILMA improved the best known solutions for 8 problem instances out of the total 24 instances.