A hybrid MOO/MCDM optimization approach to improve decision-making in multiobjective optimization

Multiobjective optimization (MOO) and multicriteria decision-making (MCDM) are critical disciplines in operations research, aiming to assist decision-makers in making the best decisions in complex problems. Nevertheless, the hybridization of the process has yet to be explored. In this case, the hybr...

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Autores:
Neira Rodado, Dionicio
Jimenez Delgado, Genett
Crespo, Fernando
Morales Espinosa, Roberto Antonio
Plazas Alvarez, Jonny Rafael
Hernandez, Hugo
Tipo de recurso:
Conferencia (Ponencia)
Fecha de publicación:
2023
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/14242
Acceso en línea:
https://hdl.handle.net/11323/14242
https://repositorio.cuc.edu.co/
Palabra clave:
MCDM
Multiobjective Optimization
Pareto set
TOPSIS
Rights
openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
Description
Summary:Multiobjective optimization (MOO) and multicriteria decision-making (MCDM) are critical disciplines in operations research, aiming to assist decision-makers in making the best decisions in complex problems. Nevertheless, the hybridization of the process has yet to be explored. In this case, the hybridization of the decision process is analyzed to evaluate the solution set obtained with this approach and compare it against the solutions obtained with Pareto Set. This novel approach shows that according to the decision-maker preferences, solutions could be in this solution set despite not being included in the Pareto Set. This approach gives alternatives to decision-makers without moving apart much from the best solution. A flow shop is used as a numerical example to compare the Pareto Set and hybrid approach outcomes.