多目标优化算法研究进展

发布时间:2024-06-07        浏览量:28

时间:2024年6月12日(星期三)13:30-14:30

地点:经管大楼A楼910

主题:多目标优化算法研究进展(Research Progress on Multi-Objective Optimization Algorithms)

主讲人:刘勇(beat365中国官方网站)

简介:刘勇,beat365中国官方网站信息管理与信息系统系副教授,硕士生导师。主要研究方向为复杂系统管理、人工智能和系统工程等。主持和参加国家自然科学基金项目、教育部人文社科项目、上海市哲学社会科学项目和上海市软科学项目等。在《Applied Soft Computing》、《Journal of Systems Engineering and Electronics》、《Expert Systems with Applications》、《管理科学学报》、《系统管理学报》、《运筹与管理》、《系统工程》、《控制理论与应用》和《控制与决策》等期刊上发表论文50余篇,出版专著3本。 

Liu Yong, Associate Professor in the Department of Information Management and Information Systems at Shanghai University of Technology, is a master's supervisor. His main research areas include complex systems management, artificial intelligence, and systems engineering. He has led and participated in projects funded by the National Natural Science Foundation of China, the Ministry of Education's Humanities and Social Sciences projects, Shanghai's Philosophy and Social Sciences projects, and Shanghai's Soft Science projects. He has published over 50 papers in journals such as Applied Soft Computing, Journal of Systems Engineering and Electronics, Expert Systems with Applications, Journal of Management Science, Journal of Systems Management, Operations Research and Management, Systems Engineering, Control Theory and Applications, and Control and Decision. He has also authored three monographs.

摘要:多目标优化是一种用于解决具有多个冲突目标问题的方法,其广泛应用于工程、经济、管理等多个领域。近年来,随着计算能力和算法理论的不断进步,多目标优化算法也取得了显著的发展。现从最新研究成果出发,简要介绍多目标优化算法的研究进展。重点包括提高算法收敛速度、处理高维和多模态问题、并行计算和动态优化等。

Multi-objective optimization is a method used to solve problems with multiple conflicting objectives, widely applied in engineering, economics, management, and other fields. In recent years, with the continuous advancement of computational power and algorithm theory, multi-objective optimization algorithms have also seen significant development. This overview introduces the latest research progress in multi-objective optimization algorithms, focusing on improving algorithm convergence speed, handling high-dimensional and multimodal problems, parallel computing, and dynamic optimization.