Trees Social Relations Optimization Algorithm: A new Swarm-Based metaheuristic technique to solve continuous and discrete optimization problems

This paper presents a new metaheuristic algorithm called Trees Social Relations Optimization Algorithm (TSR). TSR inspired by the hierarchical and collective life of trees in the jungle. The main priority of the collective consciousness of the trees is the survival of the woods. The trees try to red...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Mathematics and computers in simulation Ročník 194; s. 629 - 664
Hlavní autori: Alimoradi, Mahmoud, Azgomi, Hossein, Asghari, Ali
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.04.2022
Predmet:
Continuous optimization
Discrete optimization
Metaheuristic algorithms
Optimization
Trees Social Relations
Discrete optimization
Trees Social Relations
Continuous optimization
Optimization
Metaheuristic algorithms
ISSN:0378-4754, 1872-7166
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:This paper presents a new metaheuristic algorithm called Trees Social Relations Optimization Algorithm (TSR). TSR inspired by the hierarchical and collective life of trees in the jungle. The main priority of the collective consciousness of the trees is the survival of the woods. The trees try to reduce the damage in various ways so that the forest can develop. Organizing trees, protecting young seedlings, and their communication mechanism create a complex structure based on swarm intelligence that is the inspiration for designing an algorithm to solve existing problems. In TSR, each answer considered as a tree and a set of solutions defined as a sub-jungle. Sub-jungles are interconnected and help each other to get the right answer. The use of parallel and synchronized sub-jungles with its dedicated operators will increase the accuracy and shorten the time to reach an acceptable response. The TSR algorithm can use in continuous and discrete problems and, therefore, can use in a wide range of issues. Numerous experiments on standard and various benchmarks, as well as some classic and new issues, show that our proposed algorithm provides appropriate and acceptable answers in both time and accuracy to some similar algorithms.
ISSN:0378-4754
1872-7166
DOI:10.1016/j.matcom.2021.12.010