http://popups.lib.uliege.be/1373-5411/index.php?id=3565 Genetic Algorithms (GAs) are robust probabilistic algorithms for optimization, relying strongly on parallel computation. Their power comes from multi-point exploiting of the searching space, avoiding the stagnation in local optima. First we review the state of art in GA theory. Next, two illustrative original applications highlight the efficiency of GA on multi-parameter optimization tasks: on solving systems of fuzzy relational equations, and on optimizing the parameters involved in an economic forecasting task. Full text issues Volume 7 Fuzzy Systems, Genetic and Neural Algorithms fr Thu, 26 Sep 2024 09:59:36 +0200 Thu, 26 Sep 2024 10:00:05 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=3565 0