Fetching the paper…
Reading the bibliography…
Many traditional algorithms for solving combinatorial optimization problems involve using hand-crafted heuristics that sequentially construct a solution.
Learning heuristics over large graphs via deep reinforcement learning
S. Manchanda, A. Mittal, A. Dhawan, S. Medya, S. Ranu, and A. K. Singh · 1903
Earlier work this paper cites.
On the theory of dynamic programming
R. Bellman · 1952
Earlier work this paper cites.
Solution of a large-scale traveling-salesman problem
G. Dantzig, R. Fulkerson, and S. Johnson · 1954
Earlier work this paper cites.
A markovian decision process
R. Bellman · 1957
Earlier work this paper cites.
A method for solving traveling salesman problems
A. Croes · 1958
Earlier work this paper cites.
Integer programming formulation of traveling salesman problems
C. E. Miller, A. W. Tucker, and R. A. Zemlin · 1960
Earlier work this paper cites.
A dynamic programming approach to sequencing problems
M. Held and R. M. Karp · 1962
Earlier work this paper cites.
Scheduling of Vehicles from a Central Depot to a Number of Delivery Points
G. Clarke and J. W. Wright · 1964
Earlier work this paper cites.
Computer scheduling of vehicles from one or more depots to a number of delivery points
A. Wren and A. Holliday · 1972
Earlier work this paper cites.
An effective heuristic algorithm for the traveling-salesman problem
S. Lin and B. W. Kernighan · 1973
Earlier work this paper cites.
Worst-case analysis of a new heuristic for the travelling salesman problem
N. Christofides · 1976
Earlier work this paper cites.
Finding a maximum independent set
R. E. Tarjan and A. E. Trojanowski · 1977
Earlier work this paper cites.
On the computational complexity of ising spin glass models
F. Barahona · 1982
Earlier work this paper cites.
Linear, Integer, and Quadratic Programming with LINDO: User’s Manual , 1986
L. Schrage · 1986
Earlier work this paper cites.
IBM ILOG CPLEX optimization studio
CPLEX · 1987
Earlier work this paper cites.
Learning to predict by the methods of temporal differences
R. S. Sutton · 1988
Earlier work this paper cites.
Q-learning
C. J. Watkins and P. Dayan · 1992
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. J. Williams · 1992
Earlier work this paper cites.
An evolutionary heuristic for the maximum independent set problem
T. Back and S. Khuri · 1994
Earlier work this paper cites.
A greedy randomized adaptive search procedure for maximum independent set
T. A. Feo, M. G. Resende, and S. H. Smith · 1994
Earlier work this paper cites.
An analytical model for the container loading problem
C. Chen, S.-M. Lee, and Q. Shen · 1995
Earlier work this paper cites.
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
M. X. Goemans and D. P. Williamson · 1995
Earlier work this paper cites.
Fast discovery of association rules
R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, A. I. Verkamo, et al · 1996
Earlier work this paper cites.
Linear programming 1: Introduction
G. B. Dantzig and M. N. Thapa · 1997
Earlier work this paper cites.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Combinatorial optimization: algorithms and complexity
C. H. Papadimitriou and K. Steiglitz · 1998
Earlier work this paper cites.
Integer programming , volume 52
L. A. Wolsey · 1998
Earlier work this paper cites.
Graph-theoretic techniques for macromolecular docking
E. J. Gardiner, P. Willett, and P. J. Artymiuk · 2000
Earlier work this paper cites.
An effective implementation of the lin–kernighan traveling salesman heuristic
K. Helsgaun · 2000
Earlier work this paper cites.
Policy gradient methods for reinforcement learning with function approximation
R. S. Sutton, D. A. McAllester, S. P. Singh, and Y. Mansour · 2000
Earlier work this paper cites.
Reducibility among combinatorial problems
R. M. Karp · 2001
Earlier work this paper cites.
Snps problems, complexity, and algorithms
G. Lancia, V. Bafna, S. Istrail, R. Lippert, and R. Schwartz · 2001
Earlier work this paper cites.
Heuristic algorithms for the three-dimensional bin packing problem
A. Lodi, S. Martello, and D. Vigo · 2002
Earlier work this paper cites.
Experimental comparison of two evolutionary algorithms for the independent set problem
P. A. Borisovsky and M. S. Zavolovskaya · 2003
Earlier work this paper cites.
An improved algorithm for optimal bin packing
R. E. Korf · 2003
Earlier work this paper cites.
Variable neighborhood search for the maximum clique
P. Hansen, N. Mladenović, and D. Urošević · 2004
Earlier work this paper cites.
Multidimensional knapsack problems
H. Kellerer, U. Pferschy, and D. Pisinger · 2004
Earlier work this paper cites.
On the hardness of approximating minimum vertex cover
I. Dinur and S. Safra · 2005
Earlier work this paper cites.
An effective local search for the maximum clique problem
K. Katayama, A. Hamamoto, and H. Narihisa · 2005
Cited alongside, same era.
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
M. Mitzenmacher and E. Upfal · 2005
Cited alongside, same era.
The traveling salesman problem: a computational study
D. L. Applegate, R. E. Bixby, V. Chvatal, and W. J. Cook · 2006
Cited alongside, same era.
Dynamic local search for the maximum clique problem
W. Pullan and H. H. Hoos · 2006
Cited alongside, same era.
Combinatorial optimisation of worm propagation on an unknown network
E. Filiol, E. Franc, A. Gubbioli, B. Moquet, and G. Roblot · 2007
Cited alongside, same era.
Handbook of approximation algorithms and metaheuristics
T. F. Gonzalez · 2007
Cited alongside, same era.
Exact algorithms for maximum independent set
M. Xiao and H. Nagamochi · 2017
Later among the works it cites.
Coherent ising machines—optical neural networks operating at the quantum limit
Y. Yamamoto, K. Aihara, T. Leleu, K.-i. Kawarabayashi, S. Kako, M. Fejer, K. Inoue, and H. Takesue · 2017
Later among the works it cites.
Learning heuristics for the TSP by policy gradient
M. Deudon, P. Cournut, A. Lacoste, Y. Adulyasak, and L.-M. Rousseau · 2018
Later among the works it cites.
Learning permutations with sinkhorn policy gradient, 2018
P. Emami and S. Ranka · 2018
Later among the works it cites.
Learning generalized reactive policies using deep neural networks
E. Groshev, M. Goldstein, A. Tamar, S. Srivastava, and P. Abbeel · 2018
Later among the works it cites.
Deep q-learning from demonstrations
T. Hester, M. Vecerik, O. Pietquin, M. Lanctot, T. Schaul, B. Piot, D. Horgan, J. Quan, A. Sendonaris, I. Osband, et al · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Fast local search for the maximum independent set problem
D. V. Andrade, M. G. Resende, and R. F. Werneck · 2008
Cited alongside, same era.
Z3: An efficient smt solver
L. De Moura and N. Bjørner · 2008
Cited alongside, same era.
A better approximation ratio for the vertex cover problem
G. Karakostas · 2009
Cited alongside, same era.
Three-dimensional bin packing problem with variable bin height
Y. Wu, W. Li, M. Goh, and R. de Souza · 2010
Cited alongside, same era.
A survey of monte carlo tree search methods
C. Browne, E. Powley, D. Whitehouse, S. Lucas, P. Cowling, P. Rohlfshagen, S. Tavener, D. Perez Liebana, S. Samothrakis, and S. Colton · 2012
Cited alongside, same era.
Combinatorial optimization , volume 2
B. Korte, J. Vygen, B. Korte, and J. Vygen · 2012
Cited alongside, same era.
Later among the works it cites.
Ranked reward: Enabling self-play reinforcement learning for combinatorial optimization, 2018
A. Laterre, Y. Fu, M. K. Jabri, A.-S. Cohen, D. Kas, K. Hajjar, T. S. Dahl, A. Kerkeni, and K. Beguir · 2018
Later among the works it cites.
Reinforcement learning for solving the vehicle routing problem
M. Nazari, A. Oroojlooy, L. Snyder, and M. Takác · 2018
Later among the works it cites.
Pseudorandom sets in grassmann graph have near-perfect expansion
K. Subhash, D. Minzer, and M. Safra · 2018
Later among the works it cites.
Graph attention networks
P. Veličković, G. Cucurull, A. Casanova, A. Romero, P. Liò, and Y. Bengio · 2018
Later among the works it cites.
How powerful are graph neural networks?, 2018
K. Xu, W. Hu, J. Leskovec, and S. Jegelka · 2018
Later among the works it cites.
Graph neural networks: A review of methods and applications
J. Zhou, G. Cui, Z. Zhang, C. Yang, Z. Liu, L. Wang, C. Li, and M. Sun · 2018
Later among the works it cites.
Solving np-hard problems on graphs with extended alphago zero, 2019
K. Abe, Z. Xu, I. Sato, and M. Sugiyama · 2019
Later among the works it cites.
Reinforcement learning driven heuristic optimization
Q. Cai, W. Hang, A. Mirhoseini, G. Tucker, J. Wang, and W. Wei · 2019
Later among the works it cites.
Improving optimization bounds using machine learning: Decision diagrams meet deep reinforcement learning
Q. Cappart, E. Goutierre, D. Bergman, and L.-M. Rousseau · 2019
Later among the works it cites.
Learning to perform local rewriting for combinatorial optimization
X. Chen and Y. Tian · 2019
Later among the works it cites.
A multi-task selected learning approach for solving 3d flexible bin packing problem
L. Duan, H. Hu, Y. Qian, Y. Gong, X. Zhang, J. Wei, and Y. Xu · 2019
Later among the works it cites.
Solving combinatorial problems with machine learning methods
T. Guo, C. Han, S. Tang, and M. Ding · 2019
Later among the works it cites.
Attention, learn to solve routing problems!
W. Kool, H. van Hoof, and M. Welling · 2019
Later among the works it cites.
Destabilization of local minima in analog spin systems by correction of amplitude heterogeneity
T. Leleu, Y. Yamamoto, P. L. McMahon, and K. Aihara · 2019
Later among the works it cites.
Or-tools, 2019
L. Perron and V. Furnon · 2019
Later among the works it cites.
Mastering atari, go, chess and shogi by planning with a learned model, 2019
J. Schrittwieser, I. Antonoglou, T. Hubert, K. Simonyan, L. Sifre, S. Schmitt, A. Guez, E. Lockhart, D. Hassabis, T. Graepel, T. Lillicrap, and D. Silver · 2019
Later among the works it cites.
Annealing by simulating the coherent ising machine
E. S. Tiunov, A. E. Ulanov, and A. Lvovsky · 2019
Later among the works it cites.
Deep auto-deferring policy for combinatorial optimization, 2020
S. Ahn, Y. Seo, and J. Shin · 2020
Closest in time.
Exploratory combinatorial optimization with reinforcement learning
T. D. Barrett, W. R. Clements, J. N. Foerster, and A. Lvovsky · 2020
Closest in time.
Machine learning for combinatorial optimization: A methodological tour d’horizon
Y. Bengio, A. Lodi, and A. Prouvost · 2020
Closest in time.
Combining reinforcement learning and constraint programming for combinatorial optimization
Q. Cappart, T. Moisan, L.-M. Rousseau, I. Prémont-Schwarz, and A. Cire · 2020
Closest in time.
Learning to solve combinatorial optimization problems on real-world graphs in linear time, 2020
I. Drori, A. Kharkar, W. R. Sickinger, B. Kates, Q. Ma, S. Ge, E. Dolev, B. Dietrich, D. P. Williamson, and M. Udell · 2020
Closest in time.
A deep learning algorithm for the max-cut problem based on pointer network structure with supervised learning and reinforcement learning strategies
S. Gu and Y. Yang · 2020
Closest in time.
Gurobi optimizer reference manual, 2020
L. Gurobi Optimization · 2020
Closest in time.
Solving packing problems by conditional query learning, 2020
D. Li, C. Ren, Z. Gu, Y. Wang, and F. Lau · 2020
Closest in time.
A learning-based iterative method for solving vehicle routing problems
H. Lu, X. Zhang, and S. Yang · 2020
Closest in time.
Combinatorial optimization by graph pointer networks and hierarchical reinforcement learning
Q. Ma, S. Ge, D. He, D. Thaker, and I. Drori · 2020
Closest in time.
Co-training for policy learning
J. Song, R. Lanka, Y. Yue, and M. Ono · 2020
Closest in time.
Reinforcement learning for integer programming: Learning to cut
Y. Tang, S. Agrawal, and Y. Faenza · 2020
Closest in time.
SageMath, the Sage Mathematics Software System (Version 9.0.0) , 2020
The Sage Developers · 2020
Closest in time.
A historical note on the 3/2-approximation algorithm for the metric traveling salesman problem
R. van Bevern and V. A. Slugina · 2020
Closest in time.
Learning combinatorial optimization on graphs: A survey with applications to networking
N. Vesselinova, R. Steinert, D. F. Perez-Ramirez, and M. Boman · 2020
Closest in time.