Honey Bee Social Foraging Algorithms for Resource Allocation, Part II: Application
| dc.contributor.author | Nicanor Quijano | |
| dc.contributor.author | Kevin M. Passino | |
| dc.coverage.spatial | Bolivia | |
| dc.date.accessioned | 2026-03-22T14:43:21Z | |
| dc.date.available | 2026-03-22T14:43:21Z | |
| dc.date.issued | 2007 | |
| dc.description | Citaciones: 33 | |
| dc.description.abstract | Bioinspired solutions to technological problems exploit robust and optimal solutions evolved for biological systems via natural selection. In [1] a honey bee social foraging algorithm was introduced. It was shown that if several such algorithms ("hives") compete in the same problem domain, the strategy they use is a Nash equilibrium and that the allocation strategy is globally optimal. To illustrate the practical utility of the theoretical results and algorithm in this paper we show how it can solve a dynamic voltage allocation problem to achieve a maximum uniformly elevated temperature in an interconnected grid of temperature zones. | |
| dc.identifier.doi | 10.1109/acc.2007.4282168 | |
| dc.identifier.uri | https://doi.org/10.1109/acc.2007.4282168 | |
| dc.identifier.uri | https://andeanlibrary.org/handle/123456789/48164 | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers | |
| dc.relation.ispartof | Proceedings of the ... American Control Conference/Proceedings of the American Control Conference | |
| dc.source | Universidad de Los Andes | |
| dc.subject | Foraging | |
| dc.subject | Exploit | |
| dc.subject | Mathematical optimization | |
| dc.subject | Computer science | |
| dc.subject | Resource allocation | |
| dc.subject | Selection (genetic algorithm) | |
| dc.subject | Domain (mathematical analysis) | |
| dc.subject | Nash equilibrium | |
| dc.subject | Grid | |
| dc.subject | Resource management (computing) | |
| dc.title | Honey Bee Social Foraging Algorithms for Resource Allocation, Part II: Application | |
| dc.type | article |