A new iterated local search algorithm using genetic crossover for the traveling salesman problem
Proceedings of the 1999 ACM symposium on Applied computing
A Taxonomy of Hybrid Metaheuristics
Journal of Heuristics
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Linkage Problem, Distribution Estimation, and Bayesian Networks
Evolutionary Computation
The Hierarchical Fair Competition (HFC) Framework for Sustainable Evolutionary Algorithms
Evolutionary Computation
Biostatistical Analysis (5th Edition)
Biostatistical Analysis (5th Edition)
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
A unified view on hybrid metaheuristics
HM'06 Proceedings of the Third international conference on Hybrid Metaheuristics
An evolutionary algorithm with guided mutation for the maximum clique problem
IEEE Transactions on Evolutionary Computation
Hierarchical Iterated Local Search for the Quadratic Assignment Problem
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
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This contribution proposes a new perturbation technique for the iterated local search metaheuristic, which consists in a micro evolutionary algorithm that effectively explores the neighborhood of the solution that should undergo the perturbation operator. Its main idea is to play the same role as the standard ILS-perturbation operator, but more satisfactorily. A new model of integrative hybrid metaheuristic is obtained by incorporating the proposed perturbation approach into the iterated local search algorithm, because the evolutionary algorithm becomes a subordinate component of iterated local search. The benefits of the proposal in comparison to other iterated local search algorithms proposed in the literature to deal with binary optimization problems are experimentally shown.