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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Bibliographic Details
Published in:	Results in control and optimization Vol. 7; p. 100125
Main Authors:	Verma, Amit, Lewis, Mark
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.06.2022 Elsevier
Subjects:	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
Online Access:	Get full text
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Summary:	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