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Orchard Algorithm (OA): A new meta-heuristic algorithm for solving discrete and continuous optimization problems

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  • Kaveh, Mehrdad
  • Mesgari, Mohammad Saadi
  • Saeidian, Bahram

Abstract

Meta-heuristic algorithms have been widely used to solve different optimization problems. There have always been ongoing efforts to develop new and efficient algorithms. In this paper, the Orchard Algorithm (OA) is designed and introduced, inspired by fruit gardening. In this process, various actions such as irrigation, fertilization, trimming, and grafting lead to a fruit orchard where most trees grow and produce fruit adequately. In OA, both explorations of the search space and exploitation of the best solutions are achieved using personal and social behavior. By introducing various operators such as annual growth, screening, and grafting, the algorithm can efficiently search and explore the search space. The performance of the proposed OA algorithm was evaluated on CEC2005, IEEE CEC06 2019,test functions, and five real-world engineering problems compared with 13 widely used and competitive algorithms. Thirty benchmark functions were used to compare the capabilities of the OA algorithm with other research. The OA yields far better results in many aspects than the other algorithms. The results show the OA’s superiority and this algorithm’s capability in solving optimization problems.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:matcom:v:208:y:2023:i:c:p:95-135
    DOI: 10.1016/j.matcom.2022.12.027
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    References listed on IDEAS

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    1. Sivashan Chetty & Aderemi Adewumi, 2013. "Three new stochastic local search algorithms for continuous optimization problems," Computational Optimization and Applications, Springer, vol. 56(3), pages 675-721, December.
    2. Nibaldo Rodríguez & Abhishek Gupta & Paula L. Zabala & Guillermo Cabrera-Guerrero, 2018. "Optimization Algorithms Combining (Meta)heuristics and Mathematical Programming and Its Application in Engineering," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-3, September.
    3. Roberto Battiti & Mauro Brunato & Andrea Mariello, 2019. "Reactive Search Optimization: Learning While Optimizing," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 479-511, Springer.
    4. Pan, Jeng-Shyang & Zhang, Li-Gang & Wang, Ruo-Bin & Snášel, Václav & Chu, Shu-Chuan, 2022. "Gannet optimization algorithm : A new metaheuristic algorithm for solving engineering optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 343-373.
    5. 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.
    6. Rubinstein, Reuven Y., 1997. "Optimization of computer simulation models with rare events," European Journal of Operational Research, Elsevier, vol. 99(1), pages 89-112, May.
    7. Omid Haddad & Abbas Afshar & Miguel Mariño, 2006. "Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(5), pages 661-680, October.
    8. Hashim, Fatma A. & Houssein, Essam H. & Hussain, Kashif & Mabrouk, Mai S. & Al-Atabany, Walid, 2022. "Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 84-110.
    9. Eslami, N. & Yazdani, S. & Mirzaei, M. & Hadavandi, E., 2022. "Aphid–Ant Mutualism: A novel nature-inspired​ metaheuristic algorithm for solving optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 362-395.
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