【Academic Forum】New Wine in an Old Bottle: Classical Optimization Thought in Evolutionary Computing
Topic: New Wine in an Old Bottle: Classical Optimization Thought in Evolutionary Computing
Lecturer: Professor Zhang Qingfu, City University of Hong Kong
Host: Professor Zou Juan
Time: 10:30, July 8 (Monday), 2019
Venue: N201, XTU Engineering Building
Evolutionary computation is an important branch of computational intelligence. Its early discoveries are often inspired by natural evolution or other biological group behavior. Evolutionary computing has become an important optimization aspect of many application fields, but its theoretical development seriously lags behind. This report attempts to discuss the relationship between evolutionary and traditional optimization methods. The following topics will be discussed: 1. The relationship between genetic algorithm and gradient method; 2. The relationship between ant colony algorithm and gradient method; 3. The relationship between multi-objective evolutionary algorithm and traditional decomposition methods. An in-depth study of these relationships may play a positive role in the advancement of evolutionary computation.
Zhang Qingfu is Chair Professor of Computational Intelligence, Department of Computer Science, City University of Hong Kong, and included into Changjiang Scholar Program, Ministry of Education. He mainly studies intelligent computation, multi-objective optimization, and machine learning. His multi-objective decomposition algorithm framework has become the most commonly used framework in the field of multi-objective evolutionary computing. His mostly-cited paper in the field of multi-objective optimization is more than 3,500 times, with a total reference of nearly 17,000 times. He is an IEEE Fellow and has been selected as a high-cited scientist by Thomson Reuters for three consecutive years.