Ising Machine Approach to the Lecturer-Student Assignment Problem

Ising machines are efficient solvers for combinatorial optimization problems (COPs). After mapping COPs to Quadratic Unconstrained Binary Optimization (QUBO) problems, Ising machines search for the lowest energy solution of the QUBO corresponding to the optimal solution of the COP. Herein we propose...

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Bibliographic Details
Published in:IEEE Access Vol. 12; pp. 49752 - 49761
Main Authors: Tomita, Sora, Shirai, Tatsuhiko, Togawa, Nozomu
Format: Journal Article
Language:English
Published: Piscataway IEEE 2024
Institute of Electrical and Electronics Engineers (IEEE)
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Combinatorial analysis
Combinatorial optimization problem
Combinatorial testing
Computational modeling
Ising machine
Ising model
Mathematical models
Operations research
Optimization
Quantum annealing
QUBO
Search problems
Simulated annealing
Stationary state
Students
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:Ising machines are efficient solvers for combinatorial optimization problems (COPs). After mapping COPs to Quadratic Unconstrained Binary Optimization (QUBO) problems, Ising machines search for the lowest energy solution of the QUBO corresponding to the optimal solution of the COP. Herein we propose an efficient method to formulate a lecturer-student assignment problem as a QUBO problem. In this problem, the sets of subjects, lecturers, students, lecturers' teachable subjects, and students' required subjects are given. To minimize lecture costs, the number of lecturers in charge of students must be minimized. The number of combinations drastically increases as the number of lecturers or students increases. Using these results, we theoretically prove the optimality, i.e., the formulated QUBO takes the lowest energy if and only if the students are optimally assigned to the lecturers. Additionally, we demonstrate that an Ising machine outperforms simulated annealing in terms of solution quality and execution time.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3384980