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 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.06.2022
Elsevier |
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| Abstract | 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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| AbstractList | 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. |
| ArticleNumber | 100125 |
| Author | Verma, Amit Lewis, Mark |
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| Cites_doi | 10.15388/Informatica.2006.138 10.1016/j.asoc.2019.105485 10.1016/0097-8485(90)80007-O 10.1007/BF00934527 10.1016/S0928-4869(97)00011-6 10.1007/s10472-011-9233-2 10.1007/s00291-003-0153-3 10.1016/j.knosys.2017.11.009 10.1016/j.neucom.2016.09.122 10.1007/s11590-019-01460-7 10.1007/s10732-011-9170-6 10.1007/s10288-009-0115-y 10.1057/jors.1990.166 10.1016/S0026-2714(96)00042-X 10.1016/j.ejor.2012.07.012 10.1007/s10878-014-9734-0 10.1016/j.asoc.2013.11.008 10.1007/s10288-019-00424-y 10.1023/B:ANOR.0000039522.58036.68 |
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| Keywords | Goal seeking What if Quadratic Unconstrained Binary Optimization Quantum computer Pseudo-Boolean optimization Goal programming |
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| References | Glover, Kochenberger, Du (b3) 2019; 17 Lovász, Pelikán, Vesztergombi (b19) 2006 Hannan (b15) 1980; 18 Beasley (b23) 1990; 41 Lewis, Verma, Eckdahl (b8) 2021 Palubeckis (b21) 2006; 17 Sherali, Soyster (b26) 1983; 39 Matheson (b5) 1990; 14 Zhou, Kong, Wu, Liu, Cai, Liu (b13) 2019; 81 Verma, Lewis (b14) 2020; 14 Stadler (b16) 2002 Marques-Silva, Argelich, Graça, Lynce (b9) 2011; 62 Zangari, Pozo, Santana, Mendiburu (b11) 2017; 246 Wang, Lü, Glover, Hao (b24) 2012; 223 Glover, Lü, Hao (b22) 2010; 8 Nethercote, Stuckey, Becket, Brand, Duck, Tack (b25) 2007 Zhou, Wang, Wu, Wu (b12) 2018; 141 Arsham (b7) 1997; 37 Verma, Lewis (b18) 2020 Taguchi, Cariapa (b4) 1993 Liefooghe, Verel, Hao (b10) 2014; 16 Kochenberger, Glover, Alidaee, Rego (b1) 2004; 26 Arsham (b6) 1998; 6 Kochenberger, Hao, Glover, Lewis, Lü, Wang (b2) 2014; 28 Chicano, Alba (b17) 2013; 19 Palubeckis (b20) 2004; 131 Kochenberger (10.1016/j.rico.2022.100125_b2) 2014; 28 Hannan (10.1016/j.rico.2022.100125_b15) 1980; 18 Liefooghe (10.1016/j.rico.2022.100125_b10) 2014; 16 Chicano (10.1016/j.rico.2022.100125_b17) 2013; 19 Wang (10.1016/j.rico.2022.100125_b24) 2012; 223 Beasley (10.1016/j.rico.2022.100125_b23) 1990; 41 Verma (10.1016/j.rico.2022.100125_b18) 2020 Arsham (10.1016/j.rico.2022.100125_b6) 1998; 6 Glover (10.1016/j.rico.2022.100125_b22) 2010; 8 Taguchi (10.1016/j.rico.2022.100125_b4) 1993 Kochenberger (10.1016/j.rico.2022.100125_b1) 2004; 26 Zhou (10.1016/j.rico.2022.100125_b13) 2019; 81 Arsham (10.1016/j.rico.2022.100125_b7) 1997; 37 Nethercote (10.1016/j.rico.2022.100125_b25) 2007 Verma (10.1016/j.rico.2022.100125_b14) 2020; 14 Stadler (10.1016/j.rico.2022.100125_b16) 2002 Glover (10.1016/j.rico.2022.100125_b3) 2019; 17 Marques-Silva (10.1016/j.rico.2022.100125_b9) 2011; 62 Lovász (10.1016/j.rico.2022.100125_b19) 2006 Zhou (10.1016/j.rico.2022.100125_b12) 2018; 141 Sherali (10.1016/j.rico.2022.100125_b26) 1983; 39 Matheson (10.1016/j.rico.2022.100125_b5) 1990; 14 Palubeckis (10.1016/j.rico.2022.100125_b20) 2004; 131 Lewis (10.1016/j.rico.2022.100125_b8) 2021 Zangari (10.1016/j.rico.2022.100125_b11) 2017; 246 Palubeckis (10.1016/j.rico.2022.100125_b21) 2006; 17 |
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| SubjectTerms | Goal programming Goal seeking Pseudo-Boolean optimization Quadratic Unconstrained Binary Optimization Quantum computer What if |
| Title | Goal seeking Quadratic Unconstrained Binary Optimization |
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