On the hardness of quadratic unconstrained binary optimization problems [PDF]
Frontiers in Physics, 2022 We use exact enumeration to characterize the solutions of quadratic unconstrained binary optimization problems of less than 21 variables in terms of their distributions of Hamming distances to close-by solutions.
V. Mehta +7 more
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Goal seeking Quadratic Unconstrained Binary Optimization
Results in Control and Optimization, 2022 The Quadratic Unconstrained Binary Optimization (QUBO) modeling and solution framework is a requirement for quantum and digital annealers. However optimality for QUBO problems of any practical size is extremely difficult to achieve.
Amit Verma, Mark Lewis
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Parallelizable search-space decomposition for large-scale combinatorial optimization problems using quadratic unconstrained binary optimization [PDF]
Scientific ReportsCombinatorial optimization problems are crucial in industry. However, many COPs are NP-hard, causing the search space to grow exponentially with problem size and rendering large-scale instances computationally intractable.
Eiji Kawase +3 more
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Quadratic Unconstrained Binary Optimization for the Automotive Paint Shop Problem
IEEE Access, 2023 The Binary Paint Shop Problem (BPSP) is a combinatorial optimization problem which draws inspiration from the automotive paint shop. Its binary nature, making it a good fit for Quadratic Unconstrained Binary Optimization (QUBO) solvers, has been well ...
Pieter Debevere +2 more
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Quadratic unconstrained binary optimization problem preprocessing: Theory and empirical analysis [PDF]
Networks, 2017 The Quadratic Unconstrained Binary Optimization problem (QUBO) has become a unifying model for representing a wide range of combinatorial optimization problems, and for linking a variety of disciplines that face these problems. A new class of quantum annealing computer that maps QUBO onto a physical qubit network structure with specific size and edge ...
Fred Glover, Mark Lewis
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Digital Annealer for quadratic unconstrained binary optimization: A comparative performance analysis
Applied Soft Computing Journal, 2022 Digital Annealer (DA) is a computer architecture designed for tackling combinatorial optimization problems formulated as quadratic unconstrained binary optimization (QUBO) models. In this paper, we present the results of an extensive computational study to evaluate the performance of DA in a systematic way in comparison to multiple state-of-the-art ...
Merve Bodur, Oylum Şeker
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RisksIn this paper, we consider the inclusion of the solvency capital requirement (SCR) into portfolio optimization by the use of a quadratic proxy model. The Solvency II directive requires insurance companies to calculate their SCR based on the complete loss
Ivica Turkalj +8 more
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A smaller and more efficient one-hot encoding for QUBO [PDF]
Scientific ReportsOne-hot constraints are widely used for quadratic unconstrained binary optimization (QUBO) in quantum and simulated annealing to solve optimization problems. They correspond to exactly-one constraints for Boolean satisfiability problems (SAT), which have
Shinji Takasugi +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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A polynomial-time recursive algorithm for some unconstrained quadratic optimization problems
Discrete Applied Mathematics, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
José Neto, Walid Ben-Ameur
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