Guest Editors
Dr. Yingjun Zhang, Beijing Jiaotong University, China
Dr. Leandro Lei Minku, the University of Birmingham, UK
Dr. Liyan Song, Southern University of Science and Technology, China
Summary
Soft computing-driven decision making has drawn increasing attentions in processing uncertain decision making problems to make the existing decision and control models exceptionally adaptable and flexible. As reflected in many application fileds such as supplier selection and risk assessment, how to process uncertain information still remainsan open and important question. Soft computing methodologies have the potential to incorporate responsiveness and intelligence in various real-time applications to offer more informed decision and to control situations when facing uncertain information. This issue intends to unveil the challenging issues associated in soft computing-driven decision making applications.
We invite high-quality submissions, from both academia and industry, describing orginial and unpublished results of novel algorithms, innovative models, and critical survey. Topics of interest include, but not limited to:
Fuzzy sets for uncertain decision making,
Granular computing for uncertain decision making,
Fuzzy decision support system,
Genetic learning for decision making,
Evolutionary learning for decision making,
Uncertain online decision making; uncertain control theories
Keywords
Soft Computing; Decision Making; Fuzzy Sets; Uncertainty; Granular Computing; Genetic Learning; Evolutionary Learning
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