Comparison between the two methods of optimization: Genetic algorithm (GA) and ant colony algorithm (ACO) for the propulsion system of UAV

A propeller generates lift in the direction of revolution, similar to a revolving wing. Many previous optimization techniques exist; nevertheless, they often find optimal thrust coefficient at constant power and vice versa. Using two types algorithms, genetic algorithm (GA), ant colony (ACO), comparing with each other, this study will discover value combined obtain optimum lowest same time. Simple Blade Element Theory served as foundation for all assumptions. This article examined over 80 various designs, brands, propellers 2-blade configuration diameters ranging from 2.5 19 inches varying pitch values. The data baseline was obtained UIUC Propeller Database. inputs are type, diameter, angle, rotational speed, coefficient, coefficient. results show that by determining factor interest (FITC), can specifications. When (FITC) is 100%, ignore effect In instance 100 percent, performed much better than (ACO). But Ant more accurate algorithm.