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Engineering with Computers

Seasons optimization algorithm

  • 07-08-2020
  • Original Article
Published in:
Author
Hojjat Emami
Published in
Engineering with Computers | Issue 2/2022

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Abstract

This paper introduces a new stochastic bio-inspired optimization algorithm, denoted as seasons optimization (SO) algorithm. This algorithm is inspired by the growth cycle of trees in different seasons of a year. It is an iterative and population-based algorithm working with a population of initial solutions known as a forest. Each individual in the forest is referred to as a tree. Until the termination conditions are satisfied, the trees in the forest are updated to a new generation by applying four operators similar to the trees’ life cycles in nature: renew, competition, seeding, and resistance. These operators hopefully cause the trees to converge towards the global optimum of the optimization problem. The effectiveness of the proposed SO algorithm is evaluated using multi-variable single-objective test problems and compared with several well-known baseline and state-of-the-art algorithms. The results show that the proposed algorithm outperformed its counterparts in terms of solution quality and finding the global optimum on most benchmark functions.

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previous article Chebyshev–Gauss–Lobatto collocation method for variable-order time fractional generalized Hirota–Satsuma coupled KdV system
next article Two lopsided TSCSP (LTSCSP) iteration methods for solution of complex symmetric positive definite linear systems
Title
Seasons optimization algorithm
Author
Hojjat Emami
Publication date
07-08-2020
Publisher
Springer London
Published in
Engineering with Computers / Issue 2/2022
Print ISSN: 0177-0667
Electronic ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-020-01133-5
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