Evolutionary job scheduling with optimized population by deep reinforcement learning

Author:

Zeng Detian1,Zhan Jun1,Peng Wei1,Zeng Zengri1

Affiliation:

1. The College of Computer Science and Technology, National University of Defense Technology, Changsha, P.R. China

Funder

National Key Research and Development Program of China

National Natural Science Foundations of China

National University of Defense Technology

Publisher

Informa UK Limited

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications

Reference31 articles.

1. Bahdanau, Dzmitry, Kyunghyun Cho, and Yoshua Bengio. 2015. “Neural Machine Translation by Jointly Learning to Align and Translate.” arXiv:1409.0473.

2. Neuronlike adaptive elements that can solve difficult learning control problems

3. Bello, Irwan, Hieu Pham, Quoc V. Le, Mohammad Norouzi, and Samy Bengio. 2016. “Neural Combinatorial Optimization with Reinforcement Learning.” arXiv:1611.09940.

4. Fog computing job scheduling optimization based on bees swarm

5. Bye, Robin T., Magnus Gribbestad, Ramesh Chandra, and Ottar L. Osen. 2021. “A Comparison of GA Crossover and Mutation Methods for the Traveling Salesman Problem.” In Proceedings of Innovations in Computational Intelligence and Computer Vision (ICICV 2020), 529–542. Singapore: Springer.doi:10.1007/978-981-15-6067-5_60 .

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