Multi-Objective Optimization Technique Based on QUBO and an Ising Machine

With an increase in the complexity of society, solving multi-objective optimization problems (MOPs) has become crucial. In this study, we introduced a novel method called “quadratic unconstrained binary optimization based on the weighted normal” for solving MOPs using Ising machines, such as quantum...

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Bibliographic Details
Published in:IEEE access Vol. 12; pp. 8957 - 8969
Main Authors: Ikeda, Hiroshi, Yamazaki, Takashi
Format: Journal Article
Language:English
Published: Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
IEEE
Subjects:
algorithm
Combinatorial analysis
combinatorial optimization
Complexity
Ising model
Multi-objective optimization
Multiple objective analysis
Optimization techniques
Pareto optimization
Sustainable development
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:With an increase in the complexity of society, solving multi-objective optimization problems (MOPs) has become crucial. In this study, we introduced a novel method called “quadratic unconstrained binary optimization based on the weighted normal” for solving MOPs using Ising machines, such as quantum annealing and digital annealer (DA), in the field of combinatorial optimization. The proposed method applies the penalty-based boundary intersection method to Ising machines under a setting limited to linear objective functions and maximizes the speed and performance of the DA, which is a quadratic unconstrained binary optimization-specific solver. We demonstrated the effectiveness of the proposed method by solving a real-world problem with a nonconvex shaped Pareto front (component combination problem). The results suggested that the proposed method could handle both convex- and nonconvex-shaped Pareto fronts, expanding the potential applications of Ising machines to solving complex MOPs. This development could significantly enhance decision-making processes, particularly in achieving sustainable development goals.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3353222