Multi-objective Bonobo Optimizer with non-dominated sorting

This is Matlab code for multi-objective bonobo optimizer with non-dominated sorting and crowding distance approach (MOBO2)
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Actualizado 10 mar 2022

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This is the Matlab code for multi-objective bonobo optimizer (MOBO) with non-dominated sorting and crowding distance approach (MOBO2) . Three versions of MOBO were developed,
such as MOBO with grid-index approach (MOBO1), MOBO with non-dominated sorting and crowding distance approach (MOBO2) and MOBO with decomposition technique (MOBO3).
Among these three versions, MOBO2 approach was found to have better performances compared to other two approaches, in general.
This is written for solving unconstrained optimization problems.
However, it can also solve constrained optimization problems with constraint handling approaches.
User should write his/her own objective function and modify accordingly.
Modify the common parameters and algorithm-specific parameters as per the needs of the problem.
For details of the MOBO algorithms, kindly refer and cite as mentioned below:
Das, A.K., Nikum, A.K., Krishnan, S.V. et al. Multi-objective Bonobo Optimizer (MOBO): an intelligent heuristic for multi-criteria optimization.
Knowl Inf Syst (2020). https://doi.org/10.1007/s10115-020-01503-x
For any query, please email to: amit.besus@gmail.com

Citar como

Das, A.K., Nikum, A.K., Krishnan, S.V. et al. Multi-objective Bonobo Optimizer (MOBO): an intelligent heuristic for multi-criteria optimization. Knowl Inf Syst (2020). https://doi.org/10.1007/s10115-020-01503-x

Compatibilidad con la versión de MATLAB
Se creó con R2020a
Compatible con cualquier versión
Compatibilidad con las plataformas
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1.1.1

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1.1.0

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1.0.0