3 citations · 5 across the 6 of their papers we have counts for
6 papers
QUBO Sampling for Mixed Binary Quadratic Programming without Continuous Variable Binarization
Taisei Takabayashi, Masayuki Ohzeki
Quantum annealing and related combinatorial optimization methods typically accept quadratic unconstrained binary optimization (QUBO) problems as input, whereas many practical model…
Micro-mobility dispatch optimization via quantum annealing incorporating historical data
Takeru Goto, Masayuki Ohzeki
This paper proposes a novel dispatch formulation for micro-mobility vehicles using a Quantum Annealer (QA). In recent years, QA has gained increasing attention as a high-performanc…
Demonstration of a Compatibility-Based Childcare Support Service using Quantum Annealing
Yuuma Matsumoto, Taisei Takabayashi, Rima Sato +2
In contemporary Japan, isolated parenting has become a serious social issue, increasing psychological stress on parents and potentially affecting children's development. Existing c…
Efficient Construction of Feasible Solutions in Column Generation using Quantum Annealing
Taisei Takabayashi, Naoki Maruyama, Takuma Yoshihara +2
Column generation (CG) has been used to solve constrained 0-1 quadratic programming problems. The pricing problem, which is iteratively solved in CG, can be reduced to an unconstra…
Optimization of Connection Patterns between Mobile Phones and Base Stations using Quantum Annealing
Taisei Takabayashi, Shoichi Sudo, Toshihiro Aoki +2
In current mobile networks, optimizing which base station a mobile phone in a particular area connects to is crucial for ensuring good communication quality for each mobile phone b…
Subgradient Method using Quantum Annealing for Inequality-Constrained Binary Optimization Problems
Taisei Takabayashi, Takeru Goto, Masayuki Ohzeki
Quantum annealing is a generic solver for combinatorial optimization problems that utilizes quantum fluctuations. Recently, there has been extensive research applying quantum annea…