Fuzzy Branch-and-Bound Algorithm with OWA Operators in the Case of Consumer Decision Making

The ordered weighted averaging (OWA) operator is one of the most used techniques in the operator's aggregation procedure. This paper proposes a new assignment algorithm by using the OWA operator and different extensions of it in the Branch-and-bound algorithm. The process is based on the use of...

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Detalles Bibliográficos
Autores: Vizuete Luciano, Emilio, Bòria Reverter, Sefa, Merigó Lindahl, José M., Gil Lafuente, Anna Maria, Solé Moro, María Luisa
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/181706
Acceso en línea:https://hdl.handle.net/2445/181706
Access Level:acceso abierto
Palabra clave:Algorismes
Presa de decisions (Estadística)
Teoria d'operadors
Algorithms
Statistical decision
Operator theory
Descripción
Sumario:The ordered weighted averaging (OWA) operator is one of the most used techniques in the operator's aggregation procedure. This paper proposes a new assignment algorithm by using the OWA operator and different extensions of it in the Branch-and-bound algorithm. The process is based on the use of the ordered weighted average distance operator (OWAD) and the induced OWAD operator (IOWAD). We present it as the Branch-and-bound algorithm with the OWAD operator (BBAOWAD) and the Branch-and-bound algorithm with the IOWAD operator (BBAIOWAD). The main advantage of this approach is that we can obtain more detailed information by obtaining a parameterized family of aggregation operators. The application of the new algorithm is developed in a consumer decision-making model in the city of Barcelona regarding the selection of groceries by districts that best suit their needs. We rely on the opinion of local commerce experts in the city. The key advantage of this approach is that we can consider different sources of information independent of each other.