A Genetic Algorithm for Mixed Integer Nonlinear Programming Problems Using Separate Constraint Approximations

@inproceedings{Gantovnik2003AGA,
  title={A Genetic Algorithm for Mixed Integer Nonlinear Programming Problems Using Separate Constraint Approximations},
  author={Vladimir Gantovnik and Zafer G{\"u}rdal and Layne T. Watson and Christine M. Anderson-Cook},
  year={2003}
}
This paper describes a new approach for reducing the number of the fitness and constraint function evaluations required by a genetic algorithm (GA) for optimization problems with mixed continuous and discrete design variables. The proposed additions to the GA make the search more effective and rapidly improve the fitness value from generation to generation… CONTINUE READING