EvLib

EvLib: A parameterless self-adaptive real-valued optimisation Library. A library for optimising real-valued sets is presented, with the aim of being an easily extensible component of real applications. It uses a variety of evolutionary strategies, the parameters of which are determined at the population level using a novel recursive self-adaptive paradigm proposed in this paper. Using Object Orientated techniques it gives the ability to define an individual easily and choose an assortment of evolutionary algorithm and selection techniques.


References in zbMATH (referenced in 3 articles )

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  1. Ahandani, Morteza Alinia; Vakil-Baghmisheh, Mohammad-Taghi; Talebi, Mohammad: Hybridizing local search algorithms for global optimization (2014)
  2. Simon, Dan; Omran, Mahamed G. H.; Clerc, Maurice: Linearized biogeography-based optimization with re-initialization and local search (2014) ioport
  3. Ahandani, Morteza Alinia; Alavi-Rad, Hosein: Opposition-based learning in the shuffled differential evolution algorithm (2012) ioport