High‐throughput FPGA implementation for quadratic unconstrained binary optimization
Concurrency and Computation: Practice and Experience, 2021AbstractQuadratic unconstrained binary optimization (QUBO) is a combinatorial optimization problem. Since various NP‐hard problems such as the traveling salesman problem can be formulated as a QUBO instance, QUBO is used with a wide range of applications.
Hiroshi Kagawa +8 more
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Testing optimality for quadratic 0?1 unconstrained problems
ZOR Zeitschrift f�r Operations Research Mathematical Methods of Operations Research, 1995Summary: This paper analyses a necessary and sufficient condition for quadratic pseudo-Boolean unconstrained problems. It is proved that in general testing any necessary and sufficient optimality condition is a difficult task for any NP-hard problem. An \(\varepsilon\)-optimality condition is derived together with an approximation scheme to test it.
Paolo Carraresi +2 more
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A Collaborative Neurodynamic Algorithm for Quadratic Unconstrained Binary Optimization
IEEE Transactions on Emerging Topics in Computational IntelligenceHongzong Li, Jun Wang
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Local search heuristics for Quadratic Unconstrained Binary Optimization (QUBO)
Journal of Heuristics, 2007We present a family of local-search-based heuristics for Quadratic Unconstrained Binary Optimization (QUBO), all of which start with a (possibly fractional) initial point, sequentially improving its quality by rounding or switching the value of one variable, until arriving to a local optimum. The effects of various parameters on the efficiency of these
Endre Boros, Peter L Hammer
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A polynomial case of unconstrained zero-one quadratic optimization
Mathematical Programming, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim Allemand +3 more
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Analyzing quadratic unconstrained binary optimization problems via multicommodity flows
Discrete Applied Mathematics, 2009 Quadratic Unconstrained Binary Optimization (QUBO) problems concern the minimization of quadratic polynomials in n {0, 1}-valued variables. These problems are NP-complete, but prior work has identified a sequence of polynomial-time computable lower bounds on the minimum value, denoted by C(2), C(3), C(4),….
Robert Kleinberg
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The Use of Quadratic Regularization with a Cubic Descent Condition for Unconstrained Optimization
SIAM Journal on Optimization, 2017Summary: Cubic-regularization and trust-region methods with worst-case first-order complexity \(O(\varepsilon^{-3/2})\) and worst-case second-order complexity \(O(\varepsilon^{-3})\) have been developed in the last few years. In this paper it is proved that the same complexities are achieved by means of a quadratic-regularization method with a cubic ...
Ernesto G. Birgin, José Mario Martínez
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A polynomial-time recursive algorithm for some unconstrained quadratic optimization problems [PDF]
Discrete Applied Mathematics, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Walid Ben-Ameur, José Neto
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Quadratic Unconstrained Binary Optimization (QUBO) on neuromorphic computing system
2017 International Joint Conference on Neural Networks (IJCNN), 2017The problems of Artificial intelligence (AI) naturally maps to NP-hard optimization problems. This trend has significance to achieve human-level computation capability from machines. This computational ability can be achieved by developing evolutionary algorithms or mapping those evolutionary algorithms onto new generation computing systems: Quantum or
Md. Zahangir Alom +4 more
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Standard bi-quadratic optimization problems and unconstrained polynomial reformulations
Journal of Global Optimization, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Immanuel M. Bomze +3 more
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