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Guest Editorial: Special Issue on Engineering Applications of Memetic Computing

IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, 2012
The seven full papers and one technical correspondence in this special issue focus on the engineering applications of memetic computing.
Swagatam Das, Meng-Hiot Lim
exaly   +4 more sources

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Memetic algorithms and memetic computing optimization: A literature review

Swarm and Evolutionary Computation, 2012
Abstract Memetic computing is a subject in computer science which considers complex structures such as the combination of simple agents and memes, whose evolutionary interactions lead to intelligent complexes capable of problem-solving. The founding cornerstone of this subject has been the concept of memetic algorithms, that is a class of ...
Ferrante Neri, CARLOS Cotta
exaly   +5 more sources

Adaptive Memetic Computing for Evolutionary Multiobjective Optimization

IEEE Transactions on Cybernetics, 2015
Inspired by biological evolution, a plethora of algorithms with evolutionary features have been proposed. These algorithms have strengths in certain aspects, thus yielding better optimization performance in a particular problem. However, in a wide range of problems, none of them are superior to one another. Synergetic combination of these algorithms is
Vui Ann Shim, Kay Chen Tan
exaly   +3 more sources

Focusing the search: a progressively shrinking memetic computing framework

International Journal of Innovative Computing and Applications, 2013
An extremely natural yet efficient design pattern in memetic computing optimisation is the sequential structure algorithms composed of few simple memes executed sequentially, each one with its own specific role, have proven to be robust and versatile on various optimisation problems with diverse features and dimensionality values. This principle of non-
Giovanni Iacca, Fabio Caraffini, Ferrante Neri   +2 more
exaly   +8 more sources

A Multi-Facet Survey on Memetic Computation

IEEE Transactions on Evolutionary Computation, 2011
Memetic computation is a paradigm that uses the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving. It covers a plethora of potentially rich meme-inspired computing methodologies, frameworks and operational algorithms including simple hybrids, adaptive hybrids and memetic automaton.
Xianshun Chen, Yew-Soon Ong, Meng-Hiot Lim   +2 more
exaly   +2 more sources

Memory-saving memetic computing for path-following mobile robots

Applied Soft Computing Journal, 2013
In this paper, a recently proposed single-solution memetic computing optimization method, namely three stage optimization memetic exploration (3SOME), is used to implement a self-tuning PID controller on board of a mobile robot. More specifically, the optimal PID parameters minimizing a measure of the following error on a path-following operation are ...
Giovanni Iacca, Fabio Caraffini, Ferrante Neri   +2 more
exaly   +8 more sources

Editorial: Memetic Computing: Accelerating optimization heuristics with problem-dependent local search methods

Swarm and Evolutionary Computation, 2022
Publisher Copyright: © 2022Memetic Algorithms and, in general, approaches underneath the wider Memetic Computing paradigm, have been at the core of a frantic research activity since the very inception of this research area in the late eighties.
Eneko Osaba, Javier Del Ser, CARLOS Cotta   +2 more
exaly   +2 more sources

A Memetic Computing Approach for Unit Commitment with Energy Storage Systems

Energy Procedia, 2017
The intermittency and unpredictability of renewable energy source availability cause relevant problems in terms of grid balance and stability. Such problems can be partially solved by introducing energy storage systems (ESS), although capital costs ...
Coriolano Salvini
exaly   +2 more sources

A Computational Comparison of Memetic Differential Evolution Approaches

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015
In this paper we make a detailed computational comparison between different variants of memetic DE approaches, including the two variants Greedy MDE (G-MDE) and Distance MDE (D-MDE), recently introduced in [Cabassi & Locatelli, 2015]. The computational comparison reveals that G-MDE is quite effective over single funnel functions, while D-MDE usually ...
Federico Cabassi, Marco Locatelli 0001
openaire   +1 more source