- Session: Selection Hyper-heuristics (Submission Code: 665d9460)
- Session: Generation Hyper-heuristics (Submission Code: 2480ffb0)
Hyper-heuristics are problem-independent generic solvers which have been successfully applied to a wide range of combinatorial search problems both from academia and real-world, such as timetabling, scheduling, routing, rostering, cutting and packing. The studies on this field is mainly considered under two categories, namely Selection and Generation Hyper-heuristics. Selection Hyper-heuristics operate by automatically choosing (low-level) heuristics from an existing heuristic set while the latter type focuses on generating heuristics from scratch based on predefined components. This stream is expecting studies focusing on either of these hyper-heuristic types -offering different learning approaches, utilizing distinct (meta-) heuristic techniques while dealing with various problems.
- Dr. Rong Qu, University of Nottingham, UK
Important Dates:
-------------- Abstract Submissions:
March 19, 2018 (Extended) Notification to Authors: March 21, 2018
Early Registration: April 6, 2018
Registration: April 20, 2018
For more details:
https://mustafamisir.github.io/ss-hh.htmlBest regards,
Patrick De Causmaecker (KU Leuven)
Mustafa Misir (Nanjing University of Aeronautics and Astronautics)
Ender Ozcan (University of Nottingham)
Rong Qu (University of Nottingham)
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Mustafa MISIR
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Machine lEarning and Operations Research (MEmORy) Lab
Institute of Machine Learning and Computational Intelligence
College of Computer Science and Technology, Office: 230
Nanjing University of Aeronautics and Astronautics
29 Jiangjun Road, Jiangning, 211106 Nanjing/Jiangsu, China
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