Shahed Mohammadi
Department of Computer Science and Systems Engineering, Ayandegan University, Tonekabon, Iran
[ 1 ] - Comparative Study of Particle Swarm Optimization and Genetic Algorithm Applied for Noisy Non-Linear Optimization Problems
Optimization of noisy non-linear problems plays a key role in engineering and design problems. These optimization problems can't be solved effectively by using conventional optimization methods. However, metaheuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) seem very efficient to approach in these problems and became very popular. The efficiency of these ...
نویسندگان همکار