@inproceedings{3fa63e62ee3d43549d15c4bdcb8bc791,
title = "Solving the Set Covering Problem Using Cat Swarm Optimization Algorithm with a Variable Mixture Rate and Population Restart",
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 = "Combinatorial Optimization, Diversity loss, Metaheuristics",
author = "Broderick Crawford and Ricardo Soto and Hugo Caballero",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.; International Conference on Computational Methods in Systems and Software, CoMeSySo 2017 ; Conference date: 12-09-2017 Through 14-09-2017",
year = "2018",
doi = "10.1007/978-3-319-67621-0_14",
language = "English",
isbn = "9783319676203",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "156--166",
editor = "Radek Silhavy and Petr Silhavy and Zdenka Prokopova",
booktitle = "Applied Computational Intelligence and Mathematical Methods - Computational Methods in Systems and Software 2017",
}