f-Flip strategies for unconstrained binary quadratic programming
Unconstrained binary quadratic programming (UBQP) provides a unifying modeling and solution framework for solving a remarkable range of binary optimization problems, including many accompanied by constraints. Current methods for solving UBQP problems customarily rely on neighborhoods consisting of f...
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| Vydáno v: | Annals of operations research Ročník 238; číslo 1-2; s. 651 - 657 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
Springer US
01.03.2016
Springer Springer Nature B.V Springer Verlag |
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| ISSN: | 0254-5330, 1572-9338 |
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| Abstract | Unconstrained binary quadratic programming (UBQP) provides a unifying modeling and solution framework for solving a remarkable range of binary optimization problems, including many accompanied by constraints. Current methods for solving UBQP problems customarily rely on neighborhoods consisting of
flip moves
that select one or more binary variables and “flip” their values to the complementary value (from 1 to 0 or from 0 to 1). We introduce a class of approaches called
f-flip strategies
that include a fractional value f as one of those available to the binary variables during intermediate stages of solution. A variety of different f-flip strategies, particularly within the context of multi-start algorithms, are proposed for pursuing intensification and diversification goals in metaheuristic algorithms, accompanied by special rules for evaluating and executing f-flips efficiently. |
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| AbstractList | Unconstrained binary quadratic programming (UBQP) provides a unifying modeling and solution framework for solving a remarkable range of binary optimization problems, including many accompanied by constraints. Current methods for solving UBQP problems customarily rely on neighborhoods consisting of
flip moves
that select one or more binary variables and “flip” their values to the complementary value (from 1 to 0 or from 0 to 1). We introduce a class of approaches called
f-flip strategies
that include a fractional value f as one of those available to the binary variables during intermediate stages of solution. A variety of different f-flip strategies, particularly within the context of multi-start algorithms, are proposed for pursuing intensification and diversification goals in metaheuristic algorithms, accompanied by special rules for evaluating and executing f-flips efficiently. Unconstrained binary quadratic programming (UBQP) provides a unifying modeling and solution framework for solving a remarkable range of binary optimization problems, including many accompanied by constraints. Current methods for solving UBQP problems customarily rely on neighborhoods consisting of flip moves that select one or more binary variables and “flip” their values to the complementary value (from 1 to 0 or from 0 to 1). We introduce a class of approaches called f-flip strategies that include a fractional value f as one of those available to the binary variables during intermediate stages of solution. A variety of different f-flip strategies, particularly within the context of multi-start algorithms, are proposed for pursuing intensification and diversification goals in metaheuristic algorithms, accompanied by special rules for evaluating and executing f-flips efficiently. |
| Audience | Academic |
| Author | Hao, Jin-Kao Glover, Fred |
| Author_xml | – sequence: 1 givenname: Fred surname: Glover fullname: Glover, Fred email: fredwglover@yahoo.com organization: University of Colorado Leeds School of Business – sequence: 2 givenname: Jin-Kao surname: Hao fullname: Hao, Jin-Kao organization: LERIA, Université d’Angers, Institut Universitaire de France |
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| CitedBy_id | crossref_primary_10_3390_a16120557 crossref_primary_10_1016_j_knosys_2017_11_009 |
| Cites_doi | 10.1080/00207729408928968 10.1016/j.cor.2011.12.006 10.1007/s10878-014-9734-0 10.1504/IJMHEUR.2010.034201 10.1007/s00291-003-0153-3 10.1287/opre.36.3.493 10.1007/s10732-011-9189-8 10.1007/BFb0120827 10.1016/j.ejor.2012.07.012 10.1007/978-3-642-85823-9 10.1007/BF02115753 10.1016/j.cor.2006.04.002 10.1504/IJMHEUR.2010.033120 10.1287/opre.18.3.454 10.1007/978-1-4757-3023-4_1 |
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| Copyright | Springer Science+Business Media New York 2015 COPYRIGHT 2016 Springer Springer Science+Business Media New York 2016 Distributed under a Creative Commons Attribution 4.0 International License |
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| DOI | 10.1007/s10479-015-2076-1 |
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| Keywords | Multi-start algorithms Binary quadratic programming Computational efficiency Metaheuristics 0–1 Optimization metaheuristics |
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| References | Lewis, Kochenberger, Alidaee (CR17) 2008; 35 Kochenberger, Hao, Lü, Wang, Glover (CR13) 2013; 19 Kochenberger, Glover, Alidaee, Rego (CR12) 2004; 26 CR3 Krarup, Pruzan (CR15) 1978; 9 Kochenberger, Hao, Glover, Lewis, Lü, Wang, Wang (CR14) 2014; 28 Wang, Lü, Glover, Hao (CR18) 2012; 223 Hammer, Rudeanu (CR11) 1968 Glover, Hao (CR7) 2010; 1 Boros, Hammer (CR4) 1991; 33 Laughunn (CR16) 1970; 14 Alidaee, Kochenberger, Ahmadian (CR1) 1994; 25 Glover, Laguna, Marti, Onwubolu, Babu (CR10) 2004 Barahona, Grotschel, Junger, Reinelt (CR2) 1988; 36 Glover, Hao (CR8) 2010; 1 Gallo, Hammer, Simeone (CR6) 1980; 12 Wang, Lü, Glover, Hao (CR19) 2013; 40 Glover, Laguna, Marti (CR9) 2000; 39 Chardaire, Sutter (CR5) 1994; 4 J Krarup (2076_CR15) 1978; 9 P Chardaire (2076_CR5) 1994; 4 G Kochenberger (2076_CR14) 2014; 28 G Kochenberger (2076_CR12) 2004; 26 E Boros (2076_CR4) 1991; 33 2076_CR3 F Glover (2076_CR8) 2010; 1 F Barahona (2076_CR2) 1988; 36 GA Kochenberger (2076_CR13) 2013; 19 G Gallo (2076_CR6) 1980; 12 F Glover (2076_CR10) 2004 F Glover (2076_CR9) 2000; 39 M Lewis (2076_CR17) 2008; 35 B Alidaee (2076_CR1) 1994; 25 DJ Laughunn (2076_CR16) 1970; 14 Y Wang (2076_CR18) 2012; 223 PL Hammer (2076_CR11) 1968 F Glover (2076_CR7) 2010; 1 Y Wang (2076_CR19) 2013; 40 |
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| Title | f-Flip strategies for unconstrained binary quadratic programming |
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