PDoublePop: An implementation of parallel genetic algorithm for function optimization

Main Author: Ballantyne, John
Other Authors: Tsoulos , Ioannis G., Tzallas, Alexandros, Tsalikakis, Dimitris
Format: Dataset
Terbitan: Mendeley , 2017
Subjects:
Online Access: https:/data.mendeley.com/datasets/shf4yvshm2
Daftar Isi:
  • A software for the implementation of parallel genetic algorithms is presented in this article. The underlying genetic algorithm is aimed to locate the global minimum of a multidimensional function inside a rectangular hyperbox. The proposed software named PDoublePop implements a client–server model for parallel genetic algorithms with advanced features for the local genetic algorithms such as: an enhanced stopping rule, an advanced mutation scheme and periodical application of a local search procedure. The user may code the objective function either in C++ or in Fortran77. The method is tested on a series of well-known test functions and the results are reported.