Results 61 to 70 of about 2,742,325 (160)

Bounds for Binary Integer Programming via Unconstrained Quadratic Pseudo-Boolean Optimization

Mathematics
This research proposes a method for finding bounds in binary integer programming (BIP) and quadratic binary integer programming (QBIP). Our approach utilizes a max-flow technique within the framework of quadratic pseudo-Boolean optimization.
Sirilak Phonin, Chulin Likasiri
doaj   +1 more source

Modularity‐Preserving Hamiltonian Compression for QAOA‐Based Community Detection

Advanced Quantum Technologies, Volume 9, Issue 6, June 2026.
This work explores several quantum methods to community detection in networks by simplifying modularity‐based Hamiltonians. By reducing circuit complexity through sparsification, spectral projection, and penalty techniques, the methods retain key structural information while improving efficiency.
Danilo Cavaliere, Giuseppe Fenza, Vincenzo Loia   +2 more
wiley   +1 more source

Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates

Advanced Intelligent Systems, Volume 8, Issue 5, May 2026.
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin, Rudolf M. Füchslin, Achille Giacometti, Helmut Hauser, Marco Werner   +4 more
wiley   +1 more source

Embedding Equality Constraints of Optimization Problems into a Quantum Annealer

Algorithms, 2019
Quantum annealers such as D-Wave machines are designed to propose solutions for quadratic unconstrained binary optimization (QUBO) problems by mapping them onto the quantum processing unit, which tries to find a solution by measuring the parameters of a ...
Tomas Vyskocil, Hristo Djidjev
doaj   +1 more source

End‐to‐End Portfolio Optimization with Hybrid Quantum Annealing

Advanced Quantum Technologies, Volume 9, Issue 4, April 2026.
This works presents a hybrid quantum‐classical framework for portfolio optimization that combines quantum assisted asset selection and rebalancing with classical weight allocation. The approach processes real market data, embeds it into Quadratic Unconstrained Binary Optimization formulations, and evaluates performance within a unified workflow ...
Sai Nandan Morapakula, Sangram Deshpande, Rakesh Yata, Rushikesh Ubale, Uday Wad, Kazuki Ikeda   +5 more
wiley   +1 more source

Partitioning QUBO with two-way one-hot conditions on traveling salesman problems for city distributions with multiple clusters

Frontiers in Computer Science
We introduce a method for solving a quadratic unconstrained binary optimization (QUBO) with the two-way one-hot constraints by dividing the QUBO into parts and solving it with an Ising machine.
Akihiro Yatabe, Akihiro Yatabe
doaj   +1 more source

Qubit‐Efficient Quantum Local Search for Combinatorial Optimization

Advanced Quantum Technologies, Volume 9, Issue 3, March 2026.
We introduce a qubit‐efficient variational quantum algorithm for combinatorial optimization that adaptively uses from logarithmic to a linear number of qubits to implement quantum local search. The method encodes flip probabilities of spin groups into quantum amplitudes, enabling exploration of classically intractable neighborhoods while maintaining ...
Mikhail Podobrii, Viacheslav Kuzmin, Vladimir Voloshinov, Margarita Veshchezerova, Michael R. Perelshtein   +4 more
wiley   +1 more source

Reinforcement Learning-Based Formulations With Hamiltonian-Inspired Loss Functions for Combinatorial Optimization Over Graphs

IEEE Access
Quadratic Unconstrained Binary Optimization (QUBO) is a versatile approach used to represent a wide range of NP-hard Combinatorial Optimization (CO) problems through binary variables. The transformation of QUBO to an Ising Hamiltonian is recognized as an
Redwan Ahmed Rizvee, Raheeb Hassan, Md. Mosaddek Khan   +2 more
doaj   +1 more source

Faster QUBO Brute-Force Solving using Gray Code [PDF]

, 2023
This article describes an improved brute-force solving strategy for Quadratic Unconstrained Binary Optimization (QUBO) problems that is faster than naive approaches and easily parallelizable. It exploits the Gray code ordering of natural numbers to allow
Mücke, Sascha
core  

New QUBO Transformations to Improve Quantum and Simulated Annealing Performance for Quadratic Knapsack

Recent advances in quantum computing have shown great potential for solving combinatorial optimization problems. A notable example is the quadratic knapsack problem, a constrained binary optimization problem.
Borrajo N., Nosrati F., Fernandez A., Ramirez J. M., Aguilar J., Mancuso V.   +5 more
core   +2 more sources