4 papers
Evaluating the solution performance of the augmented Lagrangian function on Ising machines
Shunsuke Awai, Takuro Itoh, Keita Takahashi +2
We apply the augmented Lagrangian function (ALF) as a formulation for Ising machines and evaluate its performance by time-to-epsilon (\mathrm{TT\varepsilon}). The ALF has been well…
Utilizing intermediate states in quantum annealing for multi-objective optimization
Keita Takahashi, Shu Tanaka
We investigate obtaining intermediate quantum states during the quantum annealing process to address the limitation of the linear weighted sum method in multi-objective optimizatio…
Effectiveness of cardinality-return weighted maximum independent set approach for financial portfolio optimization
Keita Takahashi, Tetsuro Abe, Yasuhito Nakamura +3
The portfolio optimization problem is a critical issue in asset management and has long been studied. Markowitz's mean-variance model has fundamental limitations, such as the assum…
Quantitative analysis of the effectiveness of mid-anneal measurement in quantum annealing
Keita Takahashi, Shu Tanaka
Quantum annealing is a promising metaheuristic for solving constrained combinatorial optimization problems. However, parameter tuning difficulties and hardware noise often prevent…