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.

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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