Int. J. of Innovative Computing and Applications   »   2013 Vol.5, No.3

 

 

Title: Focusing the search: a progressively shrinking memetic computing framework

 

Authors: Ilpo Poikolainen; Giovanni Iacca; Fabio Caraffini; Ferrante Neri

 

Addresses:
Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35 (Agora), FI-40014 Jyväskylä, Finland
INCAS3 – Innovation Centre for Advanced Sensors and Sensor Systems, P.O. Box 797, 9400 AT Assen, The Netherlands
Centre for Computational Intelligence, School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester LE1 9BH, UK; Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35 (Agora), FI-40014 Jyväskylä, Finland
Centre for Computational Intelligence, School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester LE1 9BH, UK; Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35 (Agora), FI-40014 Jyväskylä, Finland

 

Abstract: 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-complexity, which can be seen as an application of the Ockham's Razor in memetic computing, leads us to create shrinking three-stage optimal memetic exploration (S-3SOME), a scheme which progressively perturbs a candidate solution by alternating three search operators, the first one being a stochastic global search, the second a random sampling within progressive narrowing hyper-volume, and the third a deterministic local search. Numerical results show that the proposed S-3SOME, despite its simplicity, is competitive not only with other memory-saving schemes recently proposed in literature, but also with complex state-of-the-art population-based algorithms characterised by high computational overhead and memory employment.

 

Keywords: resource-constrained hardware; computational intelligence optimisation; memetic computing; sequential structure algorithms; stochastic global search; random sampling; deterministic local search; memory saving.

 

DOI: 10.1504/IJICA.2013.055929

 

Int. J. of Innovative Computing and Applications, 2013 Vol.5, No.3, pp.127 - 142

 

Submission date: 10 Sep 2012
Date of acceptance: 28 Nov 2012
Available online: 16 Aug 2013

 

 

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