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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Results in control and optimization Ročník 7; s. 100125
Hlavní autori: Verma, Amit, Lewis, Mark
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.06.2022
Elsevier
Predmet:
ISSN:2666-7207, 2666-7207
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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