Multi-population adapative inflationary differential evolution

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Abstract

In this paper, a multi-population version of Adaptive Inflationary Differential Evolution, which automatically adapts the crossover probability and the differential weight of the Differential Evolution, is presented. The multi-population algorithm exploits the use of different populations, and the local minima found by each population, to assess the distance between minima; a probabilistic kernel based approach is then used to automatically adapt the dimension of a bubble in which the population is re-initialized after converging to a local minimum. The algorithm is tested on two real case functions and on two difficult academic functions.
Original languageEnglish
Pages41-54
Publication statusPublished - 13 Sep 2014
EventBio-inspired Optimization Methods and their Applications, BIOMA 14 - Ljubljana, Slovenia
Duration: 13 Sep 201413 Sep 2014

Conference

ConferenceBio-inspired Optimization Methods and their Applications, BIOMA 14
CountrySlovenia
CityLjubljana
Period13/09/1413/09/14

Keywords

  • adaptive algorithms
  • differential evolution
  • global optimization

Cite this

Di Carlo, M., Vasile, M., & Minisci, E. (2014). Multi-population adapative inflationary differential evolution. 41-54. Paper presented at Bio-inspired Optimization Methods and their Applications, BIOMA 14, Ljubljana, Slovenia.