Human Conception Optimizer (HCO)

A new nature inspired computational algorithm to solve optimization problems.
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Mise à jour 6 avr. 2023

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Computational techniques are widely used to solve complex optimization problems in different fields such as engineering, finance, biology, and so on. In this paper, the Human Conception Optimizer (HCO) is proposed as a novel metaheuristic algorithm to solve any optimization problems. The idea of this algorithm is based on some biological principles of the human conception process, such as the selective nature of cervical gel in the female reproductive system to allow only healthy sperm cells into the cervix, the guidance nature of mucus gel to help sperm track a genital tracking path towards the egg in the Fallopian tube, the asymmetric nature of flagellar movement which allows sperm cells to move in the reproductive system, the sperm hyperactivation process to make them able to fertilize an egg. Thus, the strategies pursued by the sperm in searching for the egg in the Fallopian tube are modeled mathematically. The best sperm which will meet the position of the egg will be the solution of the algorithm.

Citation pour cette source

Debasis Acharya (2024). Human Conception Optimizer (HCO) (https://www.mathworks.com/matlabcentral/fileexchange/124200-human-conception-optimizer-hco), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2015a
Compatible avec toutes les versions
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Version Publié le Notes de version
1.0.2.1

In, last version fitness function was wrongly not added. Now fitness function and the HCO with constraints are included

1.0.2

with constraints. Only change objective function and other parameters such as population number, variables, ranges etc.
In this version the constraints on population (x) during update stage are included.

1.0.1

Ready to run and see the result.

1.0.0