Search Results - "Quadratic Unconstrained Binary Optimization"

Quantum computing for future real-time building HVAC controls by Deng, Zhipeng, Wang, Xuezheng, Dong, Bing

“…•We used quantum computing to optimize model predictive control of building HVAC systems.•We formulated mixed-integer non-linear programming as quadratic…”
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Quantum annealing-based feature selection by Pranjić, Daniel, Mummaneni, Bharadwaj Chowdary, Tutschku, Christian

“…Feature selection is crucial for enhancing the accuracy and efficiency of machine learning models. This work investigates the possibility of the usefulness of…”
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Quantum computing-enhanced large-scale residential electric vehicle charging management by Deng, Zhipeng, Li, Yuewei, Wang, Xuezheng, Jiang, Zixin, Dong, Bing

“…This paper presents an innovative quantum computing framework for residential EV charging management, leveraging smart meter data and advanced quantum…”
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QUBO formulations for the graph isomorphism problem and related problems by Calude, Cristian S., Dinneen, Michael J., Hua, Richard

“…We present and compare various methods to construct efficient QUBO formulations for the Graph Isomorphism Problem—one of a very few problems in NP that is…”
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Quantum Algorithm for Higher-Order Unconstrained Binary Optimization and MIMO Maximum Likelihood Detection by Norimoto, Masaya, Mori, Ryuhei, Ishikawa, Naoki

“…In this paper, we propose a quantum algorithm that supports a real-valued higher-order unconstrained binary optimization (HUBO) problem. This algorithm is…”
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An Evolutionary Ising Optimization Framework for Unconstrained Binary Quadratic Programming by Fu, Wujie, Trivedi, Anupam, Chen, Guanyu, Gao, Yuan, Srinivasan, Dipti, Danner, Aaron

“…An Ising machine (IM), as a type of analog computer tailored for tackling intractable combinatorial optimization problems, has attracted remarkable attention…”
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Hybrid quantum annealing for large-scale exam scheduling: Validation in real-world educational scenarios by Zhou, Ziyu, Chen, Qing, Zhang, Chaojie, Tan, Mengtong, Li, Shuyan

“…This study applied the hybrid quantum annealing to address complex exam scheduling challenges in large-scale educational scenarios through hybrid quantum…”
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Penalty and partitioning techniques to improve performance of QUBO solvers by Verma, Amit, Lewis, Mark

“…Quadratic Unconstrained Binary Optimization (QUBO) modeling has become a unifying framework for solving a wide variety of both unconstrained as well as…”
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Four-Dimensional Variational Data Assimilation Using the Second-Order Incremental Approach and Quantum Annealing by Shunji KOTSUKI, Fumitoshi KAWASAKI, Tadashi TSUYUKI

“…Four-dimensional variational data assimilation (4DVar) has been used as widely as ensemble Kalman filters (EnKFs) in meteorology and oceanography. Unlike…”
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Optimization with photonic wave-based annealers by Prabhakar, A, Shah, P, Gautham, U, Natarajan, V, Ramesh, V, Chandrachoodan, N, Tayur, S

“…Many NP-hard combinatorial optimization (CO) problems can be cast as a quadratic unconstrained binary optimization model, which maps naturally to an Ising…”
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Max-flow min-cut theorem in quantum computing by Singh, Nongmeikapam Brajabidhu, Roy, Arnab, Saha, Anish Kumar

“…The max-flow min-cut theorem in graph theory states that the maximum flow of a network is equal to the minimum cut of edges of the flow network. Max-flow and…”
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Large language models enhanced graph neural architecture search for quadratic unconstrained binary optimization by Zhang, Peng, Wu, Junxian, Yang, Hong, Zhou, Chuan, Tian, Zhihong

“…Quadratic unconstrained binary optimization (QUBO) refers to a subclass of unconstrained combinatorial optimization problems where the objective is to optimize…”
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Quantum Bridge Analytics I: a tutorial on formulating and using QUBO models by Glover, Fred, Kochenberger, Gary, Du, Yu

“…Quantum Bridge Analytics relates generally to methods and systems for hybrid classical-quantum computing, and more particularly is devoted to developing tools…”
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Benchmarking the three-dimensional and the numerical three-dimensional matching problems on the D-Wave Advantage quantum annealer by Pandya, Komal, Maiti, Abyayananda

“…This paper investigates the computational performance of the Three-Dimensional Matching (3DM) and the Numerical Three-Dimensional Matching (N3DM) problems on a…”
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Towards scalable quantum annealing for pooling and blending problems: A methodological proof-of-concept by Mappas, Vasileios K., Dorneanu, Bogdan, Nolasco, Eduardo, Vassiliadis, Vassilios S., Arellano-Garcia, Harvey

“…Industrial optimization challenges, such as the pooling and blending problem (PBP), require advanced computational methods to address non-convexity and…”
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A hybrid quantum–classical algorithm for mixed-integer optimization in power systems by Ellinas, Petros, Chevalier, Samuel, Chatzivasileiadis, Spyros

“…Mixed Integer Linear Programming (MILP) can be considered the backbone of the modern power system optimization process, with a large application spectrum, from…”
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Reforming Quantum Microgrid Formation by Lin, Chaofan, Zhang, Peng, Bragin, Mikhail A., Shamash, Yacov A.

“…This letter introduces a novel compact and lossless quantum microgrid formation (qMGF) approach to achieve efficient operational optimization of the power…”
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Non-binary dynamical Ising machines for combinatorial optimization by Shukla, Aditya, Erementchouk, Mikhail, Mazumder, Pinaki

“…Dynamical Ising machines achieve accelerated solving of complex combinatorial optimization problems by remapping the convergence to the ground state of the…”
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Constrained Higher-Order Binary Optimization for Wireless Communications Systems Using Ising Machines by Zheng, Gan, Krikidis, Ioannis

“…This paper develops an algorithmic solution using Ising machines to solve large-scale higher-order binary optimization (HOBO) problems with inequality…”
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Distributed Quantum Computing for Fast Restoration of Power Distribution Systems with Grid-Forming IBRs by Lin, Chaofan, Zhang, Peng, Shamash, Yacov A.

“…The combinatorial nature of restoration decisions, especially under increased grid-forming inverter-based resources (IBRs), renders classical optimization…”
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