Results 51 to 60 of about 1,712 (186)

Multi-Objective Optimization Technique Based on QUBO and an Ising Machine

IEEE Access
With an increase in the complexity of society, solving multi-objective optimization problems (MOPs) has become crucial. In this study, we introduced a novel method called “quadratic unconstrained binary optimization based on the weighted normal ...
Hiroshi Ikeda, Takashi Yamazaki
doaj   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

f-Flip strategies for unconstrained binary quadratic programming [PDF]

, 2016
Unconstrained binary quadratic programming (UBQP) provides a unifying modeling and solution framework for solving a remarkable range of binary optimization problems, including many accompanied by constraints.
Glover, Fred, F. Glover, J.K. Hao, Hao, Jin-Kao   +3 more
core   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Efficient Algorithm for Binary Quadratic Problem by Column Generation and Quantum Annealing [PDF]

, 2023
We propose an efficient algorithm that combines column generation and quantum annealing to solve binary quadratic problems. Binary quadratic problems are difficult to solve because they are NP-hard.
Hirama, Sota, Ohzeki, Masayuki
core   +2 more sources

Quadratic versus Polynomial Unconstrained Binary Models for Quantum Optimization illustrated on Railway Timetabling [PDF]

Quantum Approximate Optimization Algorithm (QAOA) is one of the most short-term promising quantum-classical algorithm to solve unconstrained combinatorial optimization problems.
Lavignac, Marion, Bourreau, Eric, Grange, Camille, Pozzoli, Valentina   +3 more
core   +4 more sources

Speedup of high-order unconstrained binary optimization using quantum $${{\mathbb{Z}}}_{2}$$ Z 2 lattice gauge theory

Communications Physics
An important and difficult problem in optimization is the high-order unconstrained binary optimization, which can represent many optimization problems more efficiently than quadratic unconstrained binary optimization, but how to quickly solve it has ...
Bi-Ying Wang, Xiaopeng Cui, Qingguo Zeng, Yemin Zhan, Man-Hong Yung, Yu Shi   +5 more
doaj   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

A continuous reformulation of the quadratic unconstrained binary optimization problem [PDF]

, 2015
In this paper we consider the Quadratic Unconstrained Binary Optimization (QUBO) Problem. Using a suitable function and penalty parameter we can reformulate the original QUBO problem as a continuous program. It is shown that the problem of large size can
ZAPOROJAN, Sergiu, MORARU, Vasile
core  

Corporate Social Responsibility and Corporate Tax Avoidance in Europe: Evidence From the Anti‐Tax Avoidance Directives

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study examines the relationship between corporate social responsibility (CSR) and corporate tax avoidance (CTA) in the European Union, exploiting institutional variation arising from CSR disclosure regimes and the introduction of the Anti‐Tax Avoidance Directives (ATAD).
Alessandro Migliavacca
wiley   +1 more source