A review of opposition-based learning from 2005 to 2012

作者：Xu Qingzheng^*; Wang Lei; Wang Na; Hei Xinhong; Zhao Li

来源：Engineering Applications of Artificial Intelligence, 2014, 29: 1-12.

DOI：10.1016/j.engappai.2013.12.004

• Opposition-based learning
• Opposite point
• Soft computing algorithms
• Function optimization

Diverse forms of opposition are already existent virtually everywhere around us, and utilizing opposite numbers to accelerate an optimization method is a new idea. Since 2005, opposition-based learning is a fast growing research field in which a variety of new theoretical models and technical methods have been studied for dealing with complex and significant problems. As a result, an increasing number of works have thus proposed. This paper provides a survey on the state-of-the-art of research, reported in the specialized literature to date, related to this framework. This overview covers basic concepts, theoretical foundation, combinations with intelligent algorithms, and typical application fields. A number of challenges that can be undertaken to help move the field forward are discussed according to the current state of the opposition-based learning.

• 出版日期2014-3
• 单位北京理工大学; 中国人民解放军国防科学技术大学; 西安理工大学