Improving the Solving of Optimization Problems: A Comprehensive Review of Quantum Approaches
Quantum ReportsOptimization is a crucial challenge across various domains, including finance, resource allocation, and mobility. Quantum computing has the potential to redefine the way we handle complex problems by reducing computational complexity and enhancing ...
Deborah Volpe +2 more
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Lagrangian duality in quantum optimization: Overcoming QUBO limitations for constrained problems
Physical Review ResearchWe 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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Physical Review Research, 2019 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
IEEE AccessThe 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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A Polynomial-Time Algorithm for Unconstrained Binary Quadratic Optimization
, 2020 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 $P$.
openaire +2 more sources
A QUBO Model for the Traveling Salesman Problem with Time Windows
Algorithms, 2019 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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SIMPLIFIED COPOSITIVE AND LAGRANGIAN RELAXATIONS FOR LINEARLY CONSTRAINED QUADRATIC OPTIMIZATION PROBLEMS IN CONTINUOUS AND BINARY VARIABLES [PDF]
, 2017 For a quadratic optimization problem (QOP) with linear equality constraints in continuous non-negative variables and binary variables, vie propose three relaxations in simplified forms with a parameter lambda: Lagrangian, completely positive, and ...
김선영
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Multi-Objective Portfolio Optimization Using a Quantum Annealer
MathematicsIn 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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A Comparative Study on Solving Optimization Problems With Exponentially Fewer Qubits
IEEE Transactions on Quantum EngineeringVariational 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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From Electron Glasses to Quantum Machine Learning: A Study in Quadratic Unconstrained Binary Optimization [PDF]
, 2020 Quadratic unconstrained binary optimization (QUBO) problems are of paramount importance in scientific and industrial applications as many interesting non-deterministic polynomial (NP)- hard problems can be mapped to them.
Barzegar, Amin
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