Goal seeking Quadratic Unconstrained Binary Optimization

The Quadratic Unconstrained Binary Optimization (QUBO) modeling and solution framework is a requirement for quantum and digital annealers. However optimality for QUBO problems of any practical size is extremely difficult to achieve. In order to incorporate the problem-specific insights, a diverse se...

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Veröffentlicht in:Results in control and optimization Jg. 7; S. 100125
Hauptverfasser: Verma, Amit, Lewis, Mark
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.06.2022
Elsevier
Schlagworte:
Goal programming
Goal seeking
Pseudo-Boolean optimization
Quadratic Unconstrained Binary Optimization
Quantum computer
What if
Goal seeking
What if
Quadratic Unconstrained Binary Optimization
Quantum computer
Pseudo-Boolean optimization
Goal programming
ISSN:2666-7207, 2666-7207
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Zusammenfassung:The Quadratic Unconstrained Binary Optimization (QUBO) modeling and solution framework is a requirement for quantum and digital annealers. However optimality for QUBO problems of any practical size is extremely difficult to achieve. In order to incorporate the problem-specific insights, a diverse set of solutions meeting an acceptable target metric or goal is the preference in high level decision making. In this paper, we present two alternatives for goal-seeking QUBO for minimizing the deviation from a given target as well as a range of values around a target. Experimental results illustrate the efficacy of the proposed approach over Constraint Programming for quickly finding a satisficing set of solutions.
ISSN:2666-7207
2666-7207
DOI:10.1016/j.rico.2022.100125