The optimization model of the vendor selection for the joint procurement from a total cost of ownership perspective

Purpose: This paper is an attempt to establish the mathematical programming model of the vendor selection for the joint procurement from a total cost of ownership perspective. Design/methodology/approach: Fuzzy genetic algorithm is employed to solve the model, and the data set of the ball bearings p...

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Detalhes bibliográficos
Autor: Pan, Fubin
Formato: artículo
Fecha de publicación:2015
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/84210
Acesso em linha:https://hdl.handle.net/2117/84210
Access Level:acceso abierto
Palavra-chave:Fuzzy logic
Computer algorithms
Materials management -- Mathematical models
Vendor selection
Joint procurement
Fuzzy genetic algorithm
Lògica difusa
Algorismes genètics
Gestió de compres -- Models matemàtics
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions
Descrição
Resumo:Purpose: This paper is an attempt to establish the mathematical programming model of the vendor selection for the joint procurement from a total cost of ownership perspective. Design/methodology/approach: Fuzzy genetic algorithm is employed to solve the model, and the data set of the ball bearings purchasing problem is illustrated as a numerical analysis. Findings: According to the results, it can be seen that the performance of the optimization model is pretty good and can reduce the total costs of the procurement. Originality/value: The contribution of this paper is threefold. First, a literature review and classification of the published vendor selection models is shown in this paper. Second, a mathematical programming model of the vendor selection for the joint procurement from a total cost of ownership perspective is established. Third, an empirical study is displayed to illustrate the application of the proposed model to evaluate and identify the best vendors for ball bearing procurement, and the results show that it could reduce the total costs as much as twenty percent after the optimization.