Scientists employ sophisticated programs to mine and extract interesting information and knowledge from enormous databases. Intelligent knowledge, extracted from large data sets, reveals useful insights and hidden patterns. Intelligent knowledge management investigates the theoretical framework of data science and intelligent knowledge to bridge the gap between mining and knowledge management and further develops the techniques of how to identify and obtain the intelligent knowledge for decision-making.

Operations research (OR) and management science (MS) have strong influences on the development of intelligent knowledge management. Many OR methodologies and tools have been applied to knowledge sharing, knowledge organization, knowledge acquisition, and knowledge usage. It is important to synthesize the research findings of intelligent knowledge and OR with a wide range of real-life applications to support sustainable economic development.

This special volume includes both high-quality academic (theoretical or empirical) and practical papers that present current state-of-the-art results from researchers and practitioners from all related disciplines. All papers have some numerical or experimental illustrations of scientific value.

The guest editors hope that the papers published in this special volume will be of interest to academic and industrial communities by promoting high quality, novel and daring research findings. The volume provides solutions and tools to solve challenging problems faced by fellow researchers, practitioners, and students, as well as research challenges and initiatives for further research.