Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers
In this paper, a comparison among Particle swarm optimization (PSO), Bee Colony Optimization (BCO) and the Bat Algorithm (BA) is presented. In addition, a modification to the main parameters of each algorithm through an interval type-2 fuzzy logic system is presented. The main aim of using interval...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-08-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/10/3/101 |
| _version_ | 1818541975911006208 |
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| author | Frumen Olivas Leticia Amador-Angulo Jonathan Perez Camilo Caraveo Fevrier Valdez Oscar Castillo |
| author_facet | Frumen Olivas Leticia Amador-Angulo Jonathan Perez Camilo Caraveo Fevrier Valdez Oscar Castillo |
| author_sort | Frumen Olivas |
| collection | DOAJ |
| description | In this paper, a comparison among Particle swarm optimization (PSO), Bee Colony Optimization (BCO) and the Bat Algorithm (BA) is presented. In addition, a modification to the main parameters of each algorithm through an interval type-2 fuzzy logic system is presented. The main aim of using interval type-2 fuzzy systems is providing dynamic parameter adaptation to the algorithms. These algorithms (original and modified versions) are compared with the design of fuzzy systems used for controlling the trajectory of an autonomous mobile robot. Simulation results reveal that PSO algorithm outperforms the results of the BCO and BA algorithms. |
| first_indexed | 2024-12-11T22:16:08Z |
| format | Article |
| id | doaj.art-314c20368e38463f9ae4aa63523bf778 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-12-11T22:16:08Z |
| publishDate | 2017-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-314c20368e38463f9ae4aa63523bf7782022-12-22T00:48:36ZengMDPI AGAlgorithms1999-48932017-08-0110310110.3390/a10030101a10030101Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy ControllersFrumen Olivas0Leticia Amador-Angulo1Jonathan Perez2Camilo Caraveo3Fevrier Valdez4Oscar Castillo5Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22379, MexicoDivision of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22379, MexicoDivision of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22379, MexicoDivision of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22379, MexicoDivision of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22379, MexicoDivision of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22379, MexicoIn this paper, a comparison among Particle swarm optimization (PSO), Bee Colony Optimization (BCO) and the Bat Algorithm (BA) is presented. In addition, a modification to the main parameters of each algorithm through an interval type-2 fuzzy logic system is presented. The main aim of using interval type-2 fuzzy systems is providing dynamic parameter adaptation to the algorithms. These algorithms (original and modified versions) are compared with the design of fuzzy systems used for controlling the trajectory of an autonomous mobile robot. Simulation results reveal that PSO algorithm outperforms the results of the BCO and BA algorithms.https://www.mdpi.com/1999-4893/10/3/101interval type-2 fuzzy logicfootprint uncertaintybio-inspired algorithmsfuzzy controller |
| spellingShingle | Frumen Olivas Leticia Amador-Angulo Jonathan Perez Camilo Caraveo Fevrier Valdez Oscar Castillo Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers Algorithms interval type-2 fuzzy logic footprint uncertainty bio-inspired algorithms fuzzy controller |
| title | Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers |
| title_full | Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers |
| title_fullStr | Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers |
| title_full_unstemmed | Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers |
| title_short | Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers |
| title_sort | comparative study of type 2 fuzzy particle swarm bee colony and bat algorithms in optimization of fuzzy controllers |
| topic | interval type-2 fuzzy logic footprint uncertainty bio-inspired algorithms fuzzy controller |
| url | https://www.mdpi.com/1999-4893/10/3/101 |
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