Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Journal of Shanghai Jiaotong University (Science)

Numerical Computation of a Mixed-Integer Optimal Control Problem Based on Quantum Annealing

Zhe Liu, Shurong Li, Yulei Ge

Published Jul 31, 2020• 3 citations
Publisher
DOI
10.1007/s12204-020-2220-1

Related papers

A Quantum Computing Based Numerical Method for Solving Mixed-Integer Optimal Control Problems

Zhe Liu, Shurong Li

Journal of Systems Science and Complexity•Jan 12, 2021•7 citations

A parallel algorithm based on quantum annealing and double-elite spiral search for mixed-integer optimal control problems in engineering

Zhe Liu, Shurong Li, Yulei Ge

Applied Soft Computing•May 18, 2022•8 citations

A quantum computing-based numerical method of mixed-integer optimal control problems under uncertainty for alkali–surfactant–polymer flooding

Zhe Liu, Shurong Li, Yulei Ge

This article presents a numerical method based on quantum computing to solve two unresolved key issues for alkali–surfactant–polymer (ASP) flooding in oil exploitation: uncertainties affecting development planning and a switch control regarding injection oil wells. First, a fuzzy multi-objective mixed-integer optimal control model describing the mechanism of ASP flooding is established. Then, an improved possibilistic programming algorithm is presented to remove fuzziness and transform the model into a deterministic single-objective mixed-integer nonlinear programming (MINLP) model. On this basis, a bi-level quantum computing algorithm including quantum annealing and quantum ant colony algorithm is proposed to solve the MINLP and acquire the optimal mixed-integer control variables. The superiority of the proposed algorithm is verified by testing a number of benchmark examples. Finally, the numerical method based on quantum computing is adopted to solve successfully a mixed-integer optimal control problem for ASP flooding under uncertainty.

Engineering Optimization•Apr 2, 2020•12 citations

Performance of quantum annealing in solving optimization problems: A review

Sei Suzuki

The European Physical Journal Special Topics•Feb 1, 2015•8 citations

Quantum annealing computing for grid partition in large-scale power systems

Dawei Wang, Kedi Zheng, Qixin Chen +2 more

As more and more controllable devices equiped in the smart grid, the inceasing scale of binary virables brings time-consuming dimension explosion problems to traditional optimizations problems. As a parallel computing method, quantum computing is valuable for exploration to accelerate the optimization computation. The classic quantum annealer (QA) only can be used for quadratic unconstraint binary optimization (QUBO) problems. This paper is to explore a novel algorithm based on the quantum annealer for grid partition problems. It is a typical large-scale Integer Quadratic Programming (IQP) problems. The proposed quantum algorithm attemped to apply Lagrangian relaxation (LR) and alternating direction method of multipliers (ADMM), to transform an IQP problem to general format of QUBO problems. Some numerical cases of the grid partition are discussed to compare the performance of the proposed algorithm with some typical methods, thus verifing the feasibility and performance of this ADMM-QA algorithm.

IEEE International Electrical and Energy Conference (CIEEC)•May 27, 2022•2 citations

Multivariable optimization: Quantum annealing and computation

Sudip Mukherjee, Bikas K. Chakrabarti

arXiv:1408.3262•The European Physical Journal Special Topics•Feb 1, 2015•76 citations
This article presents a numerical method based on quantum computing to solve two unresolved key issues for alkali–surfactant–polymer (ASP) flooding in oil exploitation: uncertainties affecting development planning and a switch control regarding injection oil wells. First, a fuzzy multi-objective mixed-integer optimal control model describing the mechanism of ASP flooding is established. Then, an improved possibilistic programming algorithm is presented to remove fuzziness and transform the model into a deterministic single-objective mixed-integer nonlinear programming (MINLP) model. On this basis, a bi-level quantum computing algorithm including quantum annealing and quantum ant colony algorithm is proposed to solve the MINLP and acquire the optimal mixed-integer control variables. The superiority of the proposed algorithm is verified by testing a number of benchmark examples. Finally, the numerical method based on quantum computing is adopted to solve successfully a mixed-integer optimal control problem for ASP flooding under uncertainty.
As more and more controllable devices equiped in the smart grid, the inceasing scale of binary virables brings time-consuming dimension explosion problems to traditional optimizations problems. As a parallel computing method, quantum computing is valuable for exploration to accelerate the optimization computation. The classic quantum annealer (QA) only can be used for quadratic unconstraint binary optimization (QUBO) problems. This paper is to explore a novel algorithm based on the quantum annealer for grid partition problems. It is a typical large-scale Integer Quadratic Programming (IQP) problems. The proposed quantum algorithm attemped to apply Lagrangian relaxation (LR) and alternating direction method of multipliers (ADMM), to transform an IQP problem to general format of QUBO problems. Some numerical cases of the grid partition are discussed to compare the performance of the proposed algorithm with some typical methods, thus verifing the feasibility and performance of this ADMM-QA algorithm.