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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| Vydané v: | Results in control and optimization Ročník 7; s. 100125 |
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| Hlavní autori: | , |
| 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 |
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| 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. |
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| ISSN: | 2666-7207 2666-7207 |
| DOI: | 10.1016/j.rico.2022.100125 |