Evolutionary Computation for Multiobjective Optimization II
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".
Deadline for manuscript submissions: closed (30 June 2019) | Viewed by 157
Special Issue Editors
Interests: Intelligent computation; Image processing; Non-linear modelling; Intelligent control
Special Issues, Collections and Topics in MDPI journals
Interests: computer vision; robotic controls; Artificial Intelligence; system on chip; embedded system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The exploration of novel algorithms for multi-objective optimization is still an open issue in scientific fields. Although many successful cases have been reported in recent years through the use of evolutionary algorithms, the reliability and performance are highly dependent on the number of objectives. On the one hand, many evolutionary algorithms may achieve sufficient accuracy; on the other hand, the balance of complexity and real-time performance has the disadvantage of complicated computing processes. Notwithstanding these concerns, this kind of methodology is commonly applied in management, production quality control, and business strategy decision-making. In response to the latest trend in mobile platforms, this Special Issue stresses the practicality of evolutionary computing for multi-objective optimization on dynamic or embedded systems. Topics of interest include, but are not limited to, novel algorithms with sufficient reliability and real-time performance for application in the following areas:
Ambient intelligence
Biometrics authentication
Green energy
Image processing
Intelligent grid management
Intelligent transport system designs
Machine vision
Robotic control and learning
Dr. Ngai Ming Kwok
Dr. Ying-Hao Yu
Guest Editors
Manuscript Submission Information
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