中国矿业大学-学术报告

报告题目：Swarm Intelligence and Evolutionary Algorithms for

Complex Scheduling Problems

报告人：高开周，副教授

报告时间：2020年10月21日（周三）下午2:00

报告形式：腾讯会议

会议ID: 754 693 140（密码：123456）

主办单位：信息与控制工程学院

报告摘要：

In this talk, the framework of swarm intelligence (SI) and evolutionary algorithms (EA) will be introduced. The applications of SI and EA for solving the flexible job shop scheduling problems (FJSP) and traffic light scheduling problems (TLS) will be discussed. We model some constraints, e.g., new job insertion, fuzzy processing time, and design encoding and decoding strategies for two applications. Some problem-feature-based local search operators are developed to improve the performance of SI and EA. Experimental results and comparisons are shown to verify the performance of swarm and evolutionary algorithms. We solved many real-life instances and will share some of them in this presentation.

报告人简介：

Kaizhou Gao (高开周) received the Ph.D. degree from Nanyang Technological University (NTU), Singapore, in 2016. From 2015 to 2018, he was a Research Fellow with the School of Electronic and Electrical Engineering, NTU. He is currently an assistant professor with the Macau Institute of Systems Engineering, Macau University of Science and Technology. His research interests include intelligent computation, optimization, scheduling, and intelligent transportation. He has published over 100 refereed papers. He is an associate editor of international journals Swarm and Evolutionary Computation and IETCollaborative Intelligent Manufacturing.