Proactive local search based on FDC
This paper introduces a proactive version of Hill Climbing (or Local Search). It is based on the identification of the best neighborhood through the repeated application of mutations and the evaluation of theses neighborhood by using FDC (Fitness Distance Correlation). The best neighborhood is used...
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| Veröffentlicht in: | Dyna (Medellín, Colombia) Colombia), 2014-04, Vol.81 (184), p.201 |
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| creator | Moreno-Espino, Mailyn Rosete-Suárez, Alejandro |
| description | This paper introduces a proactive version of Hill Climbing (or Local Search). It is based on the identification of the best neighborhood through the repeated application of mutations and the evaluation of theses neighborhood by using FDC (Fitness Distance Correlation). The best neighborhood is used during a time window, and then the analysis is repeated. An experimental study was conducted in 28 functions on binary strings. The proposed algorithm achieves good performance compared to other metaheuristics (Evolutionary Algorithms, Great Deluge Algorithm, Threshold Accepting, and RRT). |
| doi_str_mv | 10.15446/dyna.v81n184.37303 |
| format | Article |
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| ispartof | Dyna (Medellín, Colombia), 2014-04, Vol.81 (184), p.201 |
| issn | 0012-7353 2346-2183 |
| language | eng |
| recordid | cdi_proquest_journals_1676622475 |
| source | DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| title | Proactive local search based on FDC |
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