Course Description

Course CodeCourse NameCreditsHours
6105085 Evolutionary Computing 3.0 3
Description The differences between Evolutionary Computing and conventional computing in that it obtains the near optimal solution through iterations. Because of the characteristics of the fitness functions, the evolutionary computation is more tolerable for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. As a result, the evolutionary computation can be more suitable for solving engineering problems. The origin of the evolutionary computation is from the Evolutionary Planning. Through a formal mathematic modeling, the Genetic Algorithm is proved to be used to solve optimization problems. The main focus of this course will be in Genetic Algorithm (GA) and Evolutionary Programming/Evolutionary Strategy (EP/ES). Other methods such as Particle Swarm Optimization (PSO), Simulated Anneal (SA) will also be discussed.