Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
A Memetic Approach to the Nurse Rostering Problem
Applied Intelligence
Co-evolving Memetic Algorithms: Initial Investigations
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Parallelism and evolutionary algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Meta-Lamarckian learning in memetic algorithms
IEEE Transactions on Evolutionary Computation
Classification of adaptive memetic algorithms: a comparative study
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive terrain-based memetic algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Research frontier: memetic computation-past, present & future
IEEE Computational Intelligence Magazine
Parallel island-based multiobjectivised memetic algorithms for a 2D packing problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A coevolutionary memetic particle swarm optimizer
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Journal of Global Optimization
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In recent years, there has been an increase in research activities on Memetic Algorithm (MA). MA works with memes; a meme being defined as "the basic unit of cultural transmission, or imitation" [5]. In this respect, a Memetic Algorithm essentially refers to "an algorithm that mimics the mechanisms of cultural evolution". To date, there has been significant effort in bringing MA closer to the idea of cultural evolution. In this paper we assess MAs from the perspectives of "Universal Darwinism" and "Memetics". Subsequently, we propose a Diffusion Memetic Algorithm where the memetic material is transmitted by means of non-genetic transfer. Numerical studies are presented based on some of the commonly used synthetic problems in continuous optimization.