Collection
Advances in Computational Optimization and Their Modern Applications
‘Optimization’ and ‘Computing’ are highly interconnected research domains. This intertwinement has become even more highlighted in recent years with the resurgence of learning-based approaches such as machine learning, deep learning, and reinforcement learning and the emergence of concepts including crowdsourcing, smart and connected communities/systems, and autonomous and electric vehicles in various application domains. Therefore, this special issue seeks to rapidly disseminate concise and short high-quality articles (limited to a total of ten journal pages) to the community on recent advances in computational optimization and their modern applications.
Editors
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Hadi Charkhgard
University of South Florida, U.S.A., hcharkhgard@usf.edu
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Jinkyoo Park
KAIST, Korea, jinkyoo.park@kaist.ac.kr
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Changhyun Kwon
University of South Florida, U.S.A., chkwon@usf.edu
