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The design of good heuristics or approximation algorithms for NP-hard combinatorial optimization problems often requires significant specialized knowledge and trial-and-error.
On the evolution of random graphs
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Reducibility among combinatorial problems
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Set covering algorithms using cutting planes, heuristics, and subgradient optimization: a computational study
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Learning evaluation functions to improve optimization by local search
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Solving combinatorial optimization tasks by reinforcement learning: A general methodology applied to resource-constrained scheduling
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Learning to select branching rules in the dpll procedure for satisfiability
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Statistical mechanics of complex networks
Albert, Réka and Barabási, Albert-László · 2002
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Kempe, David, Kleinberg, Jon, and Tardos, Éva · 2003
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Kleinberg, Jon and Tardos, Eva · 2006
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Johnson, David S and McGeoch, Lyle A · 2007
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Bello, Irwan, Pham, Hieu, Le, Quoc V, Norouzi, Mohammad, and Bengio, Samy · 2016
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Applegate, David L, Bixby, Robert E, Chvatal, Vasek, and Cook, William J · 2011
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CPLEX User’s Manual, Version 12.6.1, 2014
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Learning to run heuristics in tree search
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