Evaluation and Selection of Providers Procedure Based on the Hierarchical Analysis Process and a Mixed Integer/Linear Programming


Context: Organizations today must select suppliers effectively to provide a timely response to the needs of their customers and thus ensure their competitiveness. The objective of this study was to establish a systematic procedure for the selection of suppliers linking the hierarchical analysis process (AHP) and a mixed integer/linear programming (MILP).

Method: A literature review was carried out in the Science Direct, Engineering Information, ProQuest and Scopus databases, which allowed identifying the most used techniques by academics, businessperson and researchers, for the selection of suppliers. The mathematical models for the AHP and the MILP were selected. The AHP was performed by means of simulation with the Montecarlo method and the MILP was validated through sensitivity analysis. In the MILP the parameters provided by Ruiz, Mendoza and Ablanedo were used, from which it was modified for different lots quantities.

Results: The parameters that feed the MILP model were changed by the simulations when performing the AHP, the changes made to the parameters showed that the mathematical model is valid. It was possible to propose a procedure for the selection of suppliers that improves the effectiveness in decision making.

Conclusions: The selection of suppliers is an essential aspect to guarantee the quality of the products and services provided by the organizations, therefore, the proposed procedure provides criteria for the decision of the suppliers considering units, capacities, costs and lot number.


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Author Biographies

Luis Alfonso Peña Florez, Universitaria Agustiniana
Facultad de Ingeniería
Yuber Liliana Rodríguez-Rojas, Universidad Santo Tomás
Convenio Universidad Santo Tomás-ICONTEC


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How to Cite
Peña Florez, L., & Rodríguez-Rojas, Y. (2018). Evaluation and Selection of Providers Procedure Based on the Hierarchical Analysis Process and a Mixed Integer/Linear Programming. Ingeniería, 23(3). https://doi.org/10.14483/23448393.13316
Published: 2018-10-05
Industrial Engineering