Adaptive global optimization with local search
Adaptive global optimization with local search
A Memetic Approach to the Nurse Rostering Problem
Applied Intelligence
Improving flexibility and efficiency by adding parallelism to genetic algorithms
Statistics and Computing
Forking Genetic Algorithm with Blocking and Shrinking Modes (fGA)
Proceedings of the 5th International Conference on Genetic Algorithms
Structure and Performance of Fine-Grain Parallelism in Genetic Search
Proceedings of the 5th International Conference on Genetic Algorithms
Comparing Synchronous and Asynchronous Cellular Genetic Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Advanced Population Diversity Measures in Genetic Programming
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Evolutionary Computation - Special issue on magnetic algorithms
Self-Adaptive Genetic Algorithms with Simulated Binary Crossover
Evolutionary Computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Empirical investigation of the benefits of partial lamarckianism
Evolutionary Computation
Special issue on emerging trends in soft computing: memetic algorithms
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Meta-Lamarckian learning in memetic algorithms
IEEE Transactions on Evolutionary Computation
Hybrid Taguchi-genetic algorithm for global numerical optimization
IEEE Transactions on Evolutionary Computation
The exploration/exploitation tradeoff in dynamic cellular genetic algorithms
IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
Classification of adaptive memetic algorithms: a comparative study
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modelling and Simulation in Engineering
Towards a memetic feature selection paradigm
IEEE Computational Intelligence Magazine
IEEE Transactions on Evolutionary Computation
Differential evolution with self adaptive local search
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Ockham's Razor in memetic computing: Three stage optimal memetic exploration
Information Sciences: an International Journal
Estimating meme fitness in adaptive memetic algorithms for combinatorial problems
Evolutionary Computation
Using computational intelligence for large scale air route networks design
Applied Soft Computing
Implementation of cellular genetic algorithms on a CNN chip: Simulations and experimental results
International Journal of Circuit Theory and Applications
FAME, soft flock formation control for collective behavior studies and rapid games development
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
A space search optimization algorithm with accelerated convergence strategies
Applied Soft Computing
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A cellular genetic algorithm (CGA) is a decentralized form of GA where individuals in a population are usually arranged in a 2D grid and interactions among individuals are restricted to a set neighborhood. In this paper, we extend the notion of cellularity to memetic algorithms (MA), a configuration termed cellular memetic algorithm (CMA). In addition, we propose adaptive mechanisms that tailor the amount of exploration versus exploitation of local solutions carried out by the CMA. We systematically benchmark this adaptive mechanism and provide evidence that the resulting adaptive CMA outperforms other methods both in the quality of solutions obtained and the number of function evaluations for a range of continuous optimization problems.