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

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  • Alimoradi, Mahmoud
  • Azgomi, Hossein
  • Asghari, Ali

Abstract

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.

Suggested Citation

  • Alimoradi, Mahmoud & Azgomi, Hossein & Asghari, Ali, 2022. "Trees Social Relations Optimization Algorithm: A new Swarm-Based metaheuristic technique to solve continuous and discrete optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 629-664.
  • Handle: RePEc:eee:matcom:v:194:y:2022:i:c:p:629-664
    DOI: 10.1016/j.matcom.2021.12.010
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    References listed on IDEAS

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    1. Fred Glover, 1990. "Tabu Search—Part II," INFORMS Journal on Computing, INFORMS, vol. 2(1), pages 4-32, February.
    2. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    3. Ramana Pilla & Ahmad Taher Azar & Tulasichandra Sekhar Gorripotu, 2019. "Impact of Flexible AC Transmission System Devices on Automatic Generation Control with a Metaheuristic Based Fuzzy PID Controller," Energies, MDPI, vol. 12(21), pages 1-19, November.
    4. Pellerin, Robert & Perrier, Nathalie & Berthaut, François, 2020. "A survey of hybrid metaheuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 280(2), pages 395-416.
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    Cited by:

    1. Kaveh, Mehrdad & Mesgari, Mohammad Saadi & Saeidian, Bahram, 2023. "Orchard Algorithm (OA): A new meta-heuristic algorithm for solving discrete and continuous optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 95-135.

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