Total Memory Optimiser: Proof of Concept and Compromises

  • Maurice ClercEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10103)


For most usual optimisation problems, the Nearer is Better assumption is true (in probability). Classical iterative algorithms take this property into account, either explicitly or implicitly, by forgetting some information collected during the process, assuming it is not useful any more. However, when the property is not globally true, i.e. for deceptive problems, it may be necessary to keep all the sampled points and their values, and to exploit this increasing amount of information. Such a basic Total Memory Optimiser is presented here. We experimentally show that this technique can outperform classical methods on small deceptive problems. As it gets very computing time expensive when the dimension of the problem increases, a few compromises are suggested to speed it up.


Search Space Combinatorial Problem Classical Optimisers Surrogate Function Global Correlation 
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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Independent ConsultantGroisyFrance

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