Escaping Bird Search for constrained optimization

Versión 1.0.2 (5,57 KB) por M Shahrouzi
Codes are provided to solve constrained engineering problems by "Escaping Bird Search" (a new meta-heuristic) via penalty approach.
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Escaping Bird Search (EBS) is a population-based metaheuristic algorithm for global optimization. Artifical search agents are distingusihed in predator-prey pairs. The algorithm simulates challenging maneuvers between the prey (Escaping Bird) and predator (Attacking Bird) to adapt suitable flights in the search space.
EBS is among the powerful derivative-free, unit-independent and parameter-less optimization algorithms. Two simplified variants of EBS are provided in a MATLAB programming framework. This framework enables better comparison of population-based algorithms by external generation and sharing of identical initial population between the algorithms at each run.
Further reading:
Mohsen Shahrouzi, Ali Kaveh, "An efficient derivative-free optimization algorithm inspired by avian life-saving manoeuvres", Journal of Computational Science,Volume 57,2022,101483,
https://doi.org/10.1016/j.jocs.2021.101483.

Citar como

M Shahrouzi (2024). Escaping Bird Search for constrained optimization (https://www.mathworks.com/matlabcentral/fileexchange/105315-escaping-bird-search-for-constrained-optimization), MATLAB Central File Exchange. Recuperado .

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Se creó con R2014a
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Versión Publicado Notas de la versión
1.0.2

Unified framework to optimize both unconstrained and penalized cost functions
1.0.1

Comparison is activated between algorithms with different number of function evaluations at each iteration. Examples of both constrained and unconstrained functions are provided.

1.0.0