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Heuristic algorithms such as simulated annealing, Concorde, and METIS are effective and widely used approaches to find solutions to combinatorial optimization problems.
Simulated annealing
Peter JM Van Laarhoven and Emile HL Aarts. 1987 · 1987
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Simulated annealing and Boltzmann machines
Emile Aarts and Jan Korst. 1988 · 1988
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Simulated annealing algorithms: An overview
Rob A Rutenbar. 1989 · 1989
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Simulated Annealing: Practice Versus Theory
L. Ingber. 1993 · 1993
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A fast and high quality multilevel scheme for partitioning irregular graphs
George Karypis and Vipin Kumar. 1999 · 1999
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Evolutionary algorithms for reinforcement learning
David E Moriarty, Alan C Schultz, and John J Grefenstette. 1999 · 1999
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Concorde TSP Solver
David Applegate, Ribert Bixby, Vasek Chvatal, and William Cook. 2006 · 2006
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Complexity and approximation: Combinatorial optimization problems and their approximability properties
Giorgio Ausiello, Pierluigi Crescenzi, Giorgio Gambosi, Viggo Kann, Alberto Marchetti-Spaccamela, and Marco Protasi. 2012 · 2012
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Integer and combinatorial optimization
Laurence A Wolsey and George L Nemhauser. 2014 · 2014
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Neural Architecture Search with Reinforcement Learning
Barret Zoph and Quoc V. Le. 2016 · 2016
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Device Placement Optimization with Reinforcement Learning
Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, and Jeff Dean. 2017 · 2017
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Evolution strategies as a scalable alternative to reinforcement learning
Tim Salimans, Jonathan Ho, Xi Chen, Szymon Sidor, and Ilya Sutskever. 2017 · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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Evolution-Guided Policy Gradient in Reinforcement Learning. In Advances in Neural Information Processing Systems . 1188–1200
Shauharda Khadka and Kagan Tumer. 2018 · 2018
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Guided evolutionary strategies: escaping the curse of dimensionality in random search
Niru Maheswaranathan, Luke Metz, George Tucker, and Jascha Sohl-Dickstein. 2018 · 2018
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CEM-RL: Combining evolutionary and gradient-based methods for policy search
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Aloïs Pourchot and Olivier Sigaud. 2018 · 2018
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