An ising machine-based solver for visiting-route recommendation problems in amusement parks

Yosuke MUKASA, Tomoya WAKAIZUMI, Shu TANAKA, Nozomu TOGAWA

Research output: Contribution to journalArticlepeer-review

Abstract

In an amusement park, an attraction-visiting route considering the waiting time and traveling time improves visitors' satisfaction and experience. We focus on Ising machines to solve the problem, which are recently expected to solve combinatorial optimization problems at high speed by mapping the problems to Ising models or quadratic unconstrained binary optimization (QUBO) models. We propose a mapping of the visiting-route recommendation problem in amusement parks to a QUBO model for solving it using Ising machines. By using an actual Ising machine, we could obtain feasible solutions one order of magnitude faster with almost the same accuracy as the simulated annealing method for the visiting-route recommendation problem.

Original languageEnglish
Pages (from-to)1592-1600
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE104D
Issue number10
DOIs
Publication statusPublished - 2021

Keywords

  • Amusement park
  • Combinatorial optimization problem
  • Ising machine
  • Ising model
  • Quadratic unconstrained binary optimization

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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