Abstract
Nowadays, it is common to find research problems (in system biology, mobile applications, etc.) that change over time, requiring algorithms which dynamically adapt the search to the new conditions. In most of them, the utilization of some information from the past allows to quickly adapt after a change. This is the idea underlining the use of memory in this field, what involves key design issues concerning the memory content, the process of update, and the process of retrieval. In this article, we focus on global memory schemes, which are the most intuitive and popular ones, and perform an integral analysis of current design variants based on a comprehensive set of benchmarks. Results show the benefits and drawbacks of each strategy, as well as the effect of the algorithm and problem features in the memory performance.
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Acknowledgments
Authors acknowledge funds from the Spanish Ministry of Sciences and Innovation European FEDER, from the International Campus of Excellence Andalucía Tech, University of Malaga, and from the VSB-Technical University of Ostrava.
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We here ensure that there is no conflicts of interest, nor sensible human/animal information has been used in this article. We declare partial funding of this work by project number 8.06/5.47.4142 in collaboration with the VSB-Technical University of Ostrava) and UMA/FEDER project FC14-TIC36.
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Bravo, Y., Luque, G. & Alba, E. Global memory schemes for dynamic optimization. Nat Comput 15, 319–333 (2016). https://doi.org/10.1007/s11047-015-9497-2
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DOI: https://doi.org/10.1007/s11047-015-9497-2