Genetic programming approach to learning multi-pass heuristics for resource constrained job scheduling

Nguyen, Su, Thiruvady, Dhananjay, Ernst, Andreas T and Alahakoon, Damminda 2018, Genetic programming approach to learning multi-pass heuristics for resource constrained job scheduling, in GECCO '18 : Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, N.Y., pp. 1167-1174, doi: 10.1145/3205455.3205485.

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Title Genetic programming approach to learning multi-pass heuristics for resource constrained job scheduling
Author(s) Nguyen, Su
Thiruvady, Dhananjay
Ernst, Andreas T
Alahakoon, Damminda
Conference name ACM Special Interest Group on Genetic and Evolutionary Computation. Conference (2018 : Kyoto, Japan)
Conference location Kyoto, Japan
Conference dates 2018/07/15 - 2018/07/19
Title of proceedings GECCO '18 : Proceedings of the Genetic and Evolutionary Computation Conference
Editor(s) Aguirre, Hernan
Takadama, Keiki
Publication date 2018
Series ACM Special Interest Group on Genetic and Evolutionary Computation Conference
Start page 1167
End page 1174
Total pages 8
Publisher Association for Computing Machinery
Place of publication New York, N.Y.
Keyword(s) Genetic programming
Combinatorial optimisation
Scheduling
ISBN 978-1-4503-5618-3
Language eng
DOI 10.1145/3205455.3205485
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2018, Association for Computing Machinery
Persistent URL http://hdl.handle.net/10536/DRO/DU:30123058

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