TY - JOUR
T1 - Application of Ising machines and a software development for Ising machines
AU - Tanahashi, Kotaro
AU - Takayanagi, Shinichi
AU - Motohashi, Tomomitsu
AU - Tanaka, Shu
N1 - Funding Information:
Acknowledgment One of the authors (S.T.) was supported by JST, PRESTO Grant Number JPMJPR1665, Japan and JSPS KAKENHI Grant Numbers 15K17720, 15H03699.
Publisher Copyright:
hysical ©2019 Society The Author(s) of Japan
PY - 2019
Y1 - 2019
N2 - An online advertisement optimization, which can be represented by a combinatorial optimization problem is performed using D-Wave 2000Q, a quantum annealing machine. To optimize the online advertisement allocation optimization, we introduce a generalized version of the Markowitz mean-variance model which is a basic model of portfolio optimization. The obtained optimization performance using D-Wave 2000Q is higher than that using the greedy method which is a conventional method. Additionally, to conveniently use Ising machines including a quantum annealing machine, new software called PyQUBO is developed. The first half of the paper gives a review of several combinatorial optimization problems and how to represent them using the Ising model or the quadratic unconstrained binary optimization (QUBO) form. We show the results of the online advertisement allocation optimization and the explanation of PyQUBO in the last half of the paper.
AB - An online advertisement optimization, which can be represented by a combinatorial optimization problem is performed using D-Wave 2000Q, a quantum annealing machine. To optimize the online advertisement allocation optimization, we introduce a generalized version of the Markowitz mean-variance model which is a basic model of portfolio optimization. The obtained optimization performance using D-Wave 2000Q is higher than that using the greedy method which is a conventional method. Additionally, to conveniently use Ising machines including a quantum annealing machine, new software called PyQUBO is developed. The first half of the paper gives a review of several combinatorial optimization problems and how to represent them using the Ising model or the quadratic unconstrained binary optimization (QUBO) form. We show the results of the online advertisement allocation optimization and the explanation of PyQUBO in the last half of the paper.
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U2 - 10.7566/JPSJ.88.061010
DO - 10.7566/JPSJ.88.061010
M3 - Review article
AN - SCOPUS:85067283782
SN - 0031-9015
VL - 88
JO - Journal of the Physical Society of Japan
JF - Journal of the Physical Society of Japan
IS - 6
M1 - 061010
ER -