| dc.date.accessioned | 2022-05-20T20:45:06Z | |
| dc.date.accessioned | 2022-10-19T00:41:18Z | |
| dc.date.available | 2022-05-20T20:45:06Z | |
| dc.date.available | 2022-10-19T00:41:18Z | |
| dc.date.created | 2022-05-20T20:45:06Z | |
| dc.date.issued | 2017 | |
| dc.date.issued | 2017 | |
| dc.identifier | http://hdl.handle.net/10533/253871 | |
| dc.identifier | 1160455 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/4485023 | |
| dc.description.abstract | Cat swarm optimization (CSO) is a novel metaheuristic
based on swarm intelligence, presented in 2006 has demonstrated great
potential generating good results and excellent performances simulating
the behavior of domestic cats using two behavior: seeking and tracing
mode, this mode are classified using a mixture rate (MR), this parameter
finally defines the number of individuals who work by exploring
and exploiting. This work presents an improvement structure of a binary
cat swarm optimization using a total reboot of the population when loss
diversity it is detected.
Keywords: Metaheuristics · Combinatorial Optimization · Diversity
loss | |
| dc.language | eng | |
| dc.relation | Computational Methods in Systems and Software | |
| dc.relation | instname: ANID | |
| dc.relation | reponame: Repositorio Digital RI2.0 | |
| dc.rights | http://creativecommons.org/licenses/by/3.0/cl/ | |
| dc.title | Solving the Set Covering Problem Using Cat Swarm Optimization Algorithm with a Variable
Mixture Rate and Population Restart | |
