14 citations · 14 across the 4 of their papers we have counts for
4 papers
Geometric Characteristics of Subproblems in Ising-Machine-Assisted Large Neighborhood Search
Masashi Yamashita, Shu Tanaka
Large-scale quadratic unconstrained binary optimization (QUBO) formulations of constrained combinatorial optimization problems often exceed the input-size limit of present Ising ma…
Ising-Machine-Assisted Large Neighborhood Search with Flexibly Tunable Subproblem Size
Koshiro Fujimoto, Masashi Yamashita, Shu Tanaka
Ising machines are heuristic solvers for combinatorial optimization, but their solution quality can degrade when large-scale constrained problems are solved directly. Ising-machine…
Effectiveness of Binary Autoencoders for QUBO-Based Optimization Problems
Tetsuro Abe, Masashi Yamashita, Shu Tanaka
In black-box combinatorial optimization, objective evaluations are often expensive, so high quality solutions must be found under a limited budget. Factorization machine with quant…
Annealing-Assisted Column Generation for Inequality-Constrained Combinatorial Optimization Problems
Hiroshi Kanai, Masashi Yamashita, Kotaro Tanahashi +1
Ising machines are expected to solve combinatorial optimization problems faster than the existing integer programming solvers. These problems, particularly those encountered in pra…