Proceedings of the third international conference on Genetic algorithms
Adaptive global optimization with local search
Adaptive global optimization with local search
Evaluating evolutionary algorithms
Artificial Intelligence - Special volume on empirical methods
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Artificial Intelligence Review
Memetic algorithms: a short introduction
New ideas in optimization
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Journal of Global Optimization
A computationally efficient evolutionary algorithm for real-parameter optimization
Evolutionary Computation
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
A New Genetic Algorithm Using Large Mutation Rates and Population-Elitist Selection (GALME)
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
Scatter Search: Methodology and Implementations in C
Scatter Search: Methodology and Implementations in C
Evolutionary algorithms with local search for combinatorial optimization
Evolutionary algorithms with local search for combinatorial optimization
A Study on the use of "self-generation'' in memetic algorithms
Natural Computing: an international journal
Evolutionary Computation - Special issue on magnetic algorithms
Real-coded memetic algorithms with crossover hill-climbing
Evolutionary Computation - Special issue on magnetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Measuring mobility and the performance of global search algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
An Analysis of Two-Parent Recombinations for Real-Valued Chromosomes in an Infinite Population
Evolutionary Computation
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
A Comparison Study of Self-Adaptation in Evolution Strategies and Real-Coded Genetic Algorithms
Evolutionary Computation
The dispersion metric and the CMA evolution strategy
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Hybrid genetic algorithms and random linkage
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Empirical investigation of the benefits of partial lamarckianism
Evolutionary Computation
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
On self-adaptive features in real-parameter evolutionary algorithms
IEEE Transactions on Evolutionary Computation
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 tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
Evolutionary algorithms + domain knowledge = real-world evolutionary computation
IEEE Transactions on Evolutionary Computation
Evolving Problems to Learn About Particle Swarm Optimizers and Other Search Algorithms
IEEE Transactions on Evolutionary Computation
Accelerating Differential Evolution Using an Adaptive Local Search
IEEE Transactions on Evolutionary Computation
Hybrid methods using genetic algorithms for global optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Classification of adaptive memetic algorithms: a comparative study
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Fast Adaptive Memetic Algorithm for Online and Offline Control Design of PMSM Drives
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Multiobjective Memetic Algorithm Based on Particle Swarm Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Coevolving Memetic Algorithms: A Review and Progress Report
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Computers and Operations Research
Memetic algorithm with local search chaining for large scale continuous optimization problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Hybrid metaheuristics in combinatorial optimization: A survey
Applied Soft Computing
Differential evolution with self adaptive local search
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A Differential Covariance Matrix Adaptation Evolutionary Algorithm for real parameter optimization
Information Sciences: an International Journal
A simulated annealing method based on a specialised evolutionary algorithm
Applied Soft Computing
Ockham's Razor in memetic computing: Three stage optimal memetic exploration
Information Sciences: an International Journal
Evolutionary design of active free space optical networks based on digital mirror devices
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Crossover-based local search in cooperative co-evolutionary feedforward neural networks
Applied Soft Computing
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Information Sciences: an International Journal
A local multiobjective optimization algorithm using neighborhood field
Structural and Multidisciplinary Optimization
Information Sciences: an International Journal
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
An intelligent multi-restart memetic algorithm for box constrained global optimisation
Evolutionary Computation
Region based memetic algorithm for real-parameter optimisation
Information Sciences: an International Journal
An analysis on separability for Memetic Computing automatic design
Information Sciences: an International Journal
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Memetic algorithms with continuous local search methods have arisen as effective tools to address the difficulty of obtaining reliable solutions of high precision for complex continuous optimisation problems. There exists a group of continuous local search algorithms that stand out as exceptional local search optimisers. However, on some occasions, they may become very expensive, because of the way they exploit local information to guide the search process. In this paper, they are called intensive continuous local search methods. Given the potential of this type of local optimisation methods, it is interesting to build prospective memetic algorithm models with them. This paper presents the concept of local search chain as a springboard to design memetic algorithm approaches that can effectively use intense continuous local search methods as local search operators. Local search chain concerns the idea that, at one stage, the local search operator may continue the operation of a previous invocation, starting from the final configuration (initial solution, strategy parameter values, internal variables, etc.) reached by this one. The proposed memetic algorithm favours the formation of local search chains during the memetic algorithm run with the aim of concentrating local tuning in search regions showing promise. In order to study the performance of the new memetic algorithm model, an instance is implemented with CMA-ES as an intense local search method. The benefits of the proposal in comparison to other kinds of memetic algorithms and evolutionary algorithms proposed in the literature to deal with continuous optimisation problems are experimentally shown. Concretely, the empirical study reveals a clear superiority when tackling high-dimensional problems.