Results 81 to 90 of about 18,347 (178)

QUBO Formulation Using Sequence Pair With Search Space Restriction for Rectangle Packing Problem

IEEE Access
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, Keisuke Otaki, Tadayoshi Matsumori, Hiroaki Yoshida, Kotaro Terada, Nozomu Togawa   +5 more
doaj   +1 more source

Analysis of the relation between quadratic unconstrained binary optimization and the spin-glass ground-state problem

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
doaj   +1 more source

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, Theodore Andronikos, Konstantinos Giannakis, Georgia Theocharopoulou, Sofia Fanarioti   +4 more
doaj   +1 more source

Application of Quantum Annealing to Nurse Scheduling Problem

, 2019
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., Ikeda, Kazuki, Nakamura, Yuma   +2 more
core  

Iterated Tabu Search for the Unconstrained Binary Quadratic Optimization Problem [PDF]

Informatica, 2006
Given a set of objects with profits (any, even negative, numbers) assigned not only to separate objects but also to pairs of them, the unconstrained binary quadratic optimization problem consists in finding a subset of objects for which the overall profit is maximized.
openaire   +1 more source

Multi-Objective Portfolio Optimization Using a Quantum Annealer

Mathematics
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, Jins de Jong, Frank Phillipson, Skander Taamallah, Mischa Vos   +4 more
doaj   +1 more source

Energy landscape structure of small graph isomorphism under variational optimization [PDF]

AIP Advances
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, Shah Ishmam Mohtashim, Akash Kundu   +2 more
doaj   +1 more source

A Comparative Study on Solving Optimization Problems With Exponentially Fewer Qubits

IEEE Transactions on Quantum Engineering
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, Nicola Franco, Jeanette Miriam Lorenz   +2 more
doaj   +1 more source

On some features of quadratic unconstrained binary optimization with random coefficients

Bollettino dell'Unione Matematica Italiana
Abstract Quadratic Unconstrained Binary Optimization (QUBO or UBQP) is concerned with maximizing/minimizing the quadratic form $$H(J, \eta ) = W \sum _{i,j} J_{i,j} \eta _{i} \eta _{j}$$ H ...
Isopi, Marco, Scoppola, Benedetto, Troiani, Alessio   +2 more
openaire   +5 more sources

Problem-structure-informed quantum approximate optimization for large-scale unit commitment with limited qubits

iEnergy
As power systems expand, solving the unit commitment problem (UCP) becomes increasingly challenging due to the curse of dimensionality, and traditional methods often struggle to balance computational efficiency and solution optimality.
Jingxian Zhou, Ziqing Zhu, Linghua Zhu, Siqi Bu   +3 more
doaj   +1 more source