Results 91 to 100 of about 18,556 (186)
Quantum annealing and its variants: application to quadratic unconstrained binary optimization
Published by RWTH Aachen University ...
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Lagrangian duality in quantum optimization: Overcoming QUBO limitations for constrained problems
We propose an approach to solving constrained combinatorial optimization problems based on embedding the concept of Lagrangian duality into the framework of adiabatic quantum computation.
Einar Gabbassov +2 more
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We analyze the transformation of quadratic unconstrained binary optimization (QUBO) from its conventional Boolean presentation into an equivalent spin-glass problem with coupled ±1 spin variables exposed to a site-dependent external field.
Stefan Boettcher
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QUBO Formulation Using Sequence Pair With Search Space Restriction for Rectangle Packing Problem
The development of quantum annealing has stimulated interest in solving NP-hard problems, including various industrial problems, such as quadratic unconstrained binary optimization (QUBO), with specialized solvers.
Akihisa Okada +5 more
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Application of Quantum Annealing to Nurse Scheduling Problem
Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice.
Humble, Travis S. +2 more
core
A Polynomial-Time Algorithm for Unconstrained Binary Quadratic Optimization
In this paper, an exact algorithm in polynomial time is developed to solve unrestricted binary quadratic programs. The computational complexity is $O\left( n^{\frac{15}{2}}\right) $, although very conservative, it is sufficient to prove that this minimization problem is in the complexity class $P$.
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A QUBO Model for the Traveling Salesman Problem with Time Windows
This work focuses on expressing the TSP with Time Windows (TSPTW for short) as a quadratic unconstrained binary optimization (QUBO) problem. The time windows impose time constraints that a feasible solution must satisfy. These take the form of inequality
Christos Papalitsas +4 more
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Multi-Objective Portfolio Optimization Using a Quantum Annealer
In this study, the portfolio optimization problem is explored, using a combination of classical and quantum computing techniques. The portfolio optimization problem with specific objectives or constraints is often a quadratic optimization problem, due to
Esteban Aguilera +4 more
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Energy landscape structure of small graph isomorphism under variational optimization [PDF]
We investigate a quadratic unconstrained binary optimization formulation of the graph isomorphism problem using the quantum approximate optimization algorithm and the variational quantum eigensolver.
Turbasu Chatterjee +2 more
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A Comparative Study on Solving Optimization Problems With Exponentially Fewer Qubits
Variational quantum optimization algorithms, such as the variational quantum eigensolver (VQE) or the quantum approximate optimization algorithm (QAOA), are among the most studied quantum algorithms.
David Winderl +2 more
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