MultiObjective Genetic Modified Algorithm (MOGMA)

Multiobjective optimization based on genetic algorithms and Pareto based approaches in solving multiobjective optimization problems is discussed in the paper. A Pareto based fitness assignment is used − non-dominated ranking and movement of a population towards the Pareto front in a multiobjective optimization problem. A MultiObjective Genetic Modified Algorithm (MOGMA) is proposed, which is an improvement of the existing algorithm.

eISSN:: 1314-4081
ISSN:: 1311-9702
Langue:: Anglais

Périodicité:: 4 fois par an
Sujets de la revue:: Computer Sciences, Information Technology

RSS Feed de la revue

MultiObjective Genetic Modified Algorithm (MOGMA)

Publié en ligne: 16 mars 2013

Pages: 23 - 33

DOI: https://doi.org/10.2478/cait-2012-0010

Mots clésMultiobjective optimization, genetic algorithms, population, Pareto based approaches, ideal point, ideal function, MultiObjective Genetic Modified Algorithm

This content is open access.

Mots clés
Multiobjective optimization, genetic algorithms, population, Pareto based approaches, ideal point, ideal function, MultiObjective Genetic Modified Algorithm