Una metodología basada en números difusos para la evaluación de criterios evaluables mediante un juicio de valor =A methodology based on fuzzy numbers for the evaluation of evaluable criteria through a value judgment

José Luis Fuentes Bargues, Mª Carmen González Cruz, Laura Ruíz Álvarez, Rafael Ernesto Prieto-Gómez


doi:10.20868/ade.2017.3571

Abstract


Resumen

La adjudicación de un contrato por parte de una administración pública depende de criterios de adjudicación evaluables mediante fórmulas y de criterios evaluables mediante juicios de valor. Los primeros disponen de fórmulas definidas mientras que los segundos siempre tienen un sesgo subjetivo porque dependen del técnico que realiza la valoración. Con objeto de minimizar las consecuencias de las arbitrariedades o incertidumbres en la evaluación de los criterios evaluables mediante un juicio de valor se puede recurrir a la lógica difusa. La lógica difusa, borrosa o fuzzy es el razonamiento matemático que permite calcular de forma exacta las magnitudes correspondientes a conceptos vagos o situaciones poco previsibles para poder tener control sobre ellas. El objetivo del presente trabajo es desarrollar una metodología que permita a los órganos de contratación la evaluación de los criterios evaluables mediante un juicio de valor mediante la utilización de la lógica difusa.

Abstract

The award of a contract by a public administration depends on criteria assessed by formulae and criteria assessed by value judgements. For the former, various predetermined formulae can be employed while for the criteria assessed by value judgements will always contain some subjective bias by the individual who performs the evaluation. In order to minimize the consequences of the arbitrariness or uncertainties in the evaluation of criteria assessed by value judgments is possible to use the fuzzy logic. Diffuse, fuzzy or fuzzy logic is the mathematical reasoning that allows to calculate accurately the magnitudes corresponding to vague concepts or situations that are not very predictable to have control over them. The objective of this paper is to show a methodology which permits to the contracting authority to evaluate the criteria assessed by value judgments through fuzzy numbers.


Keywords


Lógica difusa; Contratación pública; Juicio de Valor; Fuzzy logic; Public procurement; Value judgement

References


Ballesteros-Pérez, P., González-Cruz, M.C., Pastor-Ferrando, J.P., Fernández-Diego, M. (2012). The iso-Score Curve Graph. A new tool for competitive bidding. Automation in Construction, 22, 481-490. https://doi.org/10.1016/j.autcon.2011.11.007

Ballesteros-Pérez, P., González-Cruz, M.C., Cañavate-Grimal, A. (2013). On competitive bidding: Scoring and position probability graphs. International Journal of Project Management, 31(3), 434-448. https://doi.org/10.1016/j.ijproman.2012.09.012

Ballesteros-Pérez, P., González-Cruz, M.C., Cañavate-Grimal, A., Pellicer, E. (2013). Detecting abnormal and collusive bids in capped tendering. Automation in construction, 31, 215-229.

https://doi.org/10.1016/j.autcon.2012.11.036

Bendaña, R., Del Caño, A., De la Cruz, P. (2008). Contractor selection: fuzzy control approach. Canadian Journal of Civil Engineering, 35 (5), 473-486. https://doi.org/10.1139/L07-127

Dubois, D., Prade, H. (1994). Fuzzy Sets: A Convenient Fiction for Modeling Vagueness and Possibility. IEEE Transactions on Fuzzy Systems, Vol. 2, 6-21. https://doi.org/10.1109/91.273117

España (2011). Real Decreto Legislativo 3/2011, de 14 de Noviembre, por el que se aprueba el Texto Refundido de la Ley de Contratos del Sector Público. Boletín Oficial del Estado, núm. 276, 16 Noviembre 2011, 117729-117914.

European Union (2014). Directive 2014/24/CE of the European Parliament and of the Council of 26th February 2014, on public procurement and repealing Directive 2004/18/EC. Official Journal of the European Union, 28th March 2014, L 94, 65-242.

Fuentes-Bargues, J.L., González-Gaya, C., González-Cruz, M.C. (2015). La contratación pública de obras: situación actual y puntos de mejora. Informes de la Construcción, Vol. 67, nº 537. http://dx.doi.org/10.3989/ic.12.130. https://doi.org/10.3989/ic.12.130

Fuentes-Bargues, J.L., González-Gaya, C. (2013). Analysis of the Scoring Formula of Economic Criteria in Public Procurement. International Journal of Economic Behavior and Organization, 1(1), 1-12. https://doi.org/10.11648/j.ijebo.20130101.11

Fuentes-Bargues, J.L., González-Gaya, C. (2013). Determination of Disproportionate Tenders in Public Procurement. Journal of Investment and Management, Vol. 2, No. 1, 1-9. https://doi.org/10.11648/j.jim.20130201.11

Fuentes Bargues, J.L. (2013). Propuesta metodológica para la determinación del criterio de adjudicación económico de los concursos públicos. Madrid, Escuela Técnica Superior de Ingenieros Industriales de la Universidad Nacional de Educación a Distancia (UNED).

GTD (2006). Global Trade Negotations. Obtenido de: . Acceso: Septiembre 2013.

Lam, K.C., Ng, S.T., Tiesong, H., Skitmore, M., Cheung, S.O. (2000). Decision support system for contractor pre-qualification-artificial neural network model. Engineering Construction and Architectural Management, 7 (3), 251-266. https://doi.org/10.1046/j.1365-232X.2000.00156.x

https://doi.org/10.1108/eb021150 https://doi.org/10.1111/j.1365-232X.2000.00156.x

Nguyen, V.U. (1985). Tender evaluation by fuzzy sets. Journal of construction Engineering and Management, 111, 231 - 243. https://doi.org/10.1061/(ASCE)0733-9364(1985)111:3(231)

Nieto-Morote, A., Ruz-Vila, F. (2012). A fuzzy multi-criteria decision-making model for construction contractor prequalification. Automation in Construction, 25, 8-19. https://doi.org/10.1016/j.autcon.2012.04.004

OECD Observer (2009) (Organisation for Economic Co-operation and Development).. Bribery in Procurement, Methods, Actors and Counter-Measures.

Skitmore, R. (2002). Identifying non-competitive bids in construction contract auctions. OMEGA: International Journal of Management Science, 30, 443-449. https://doi.org/10.1016/S0305-0483(02)00057-9

Waara F., Bröchner J., (2006). Price and Nonprice Criteria for Contractor Selection. Journal of Construction Engineering and Management, 132(8), 797-804. https://doi.org/10.1061/(ASCE)0733-9364(2006)132:8(797)

Wong J.M.W., Chiang Y.H., Ng T.S. (2008). Construction and economic development: the case of Hong Kong. Construction Management and Economics, 26(8), 813-824. https://doi.org/10.1080/01446190802189927

Yager, R.R. (1980). On a general class of fuzzy connectives. Fuzzy Sets & Systems, 4, 235-242.

https://doi.org/10.1016/0165-0114(80)90013-5

Zadeh, L.A. (1965). Fuzzy sets. Information Control, 8, 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X

Zadeh, L. A. (1975). The concept of a linguistic variable and its applications to approximate reasoning. Part I. Information Science, 8, 199-249; Part II. Information Science Vol. 8, 301-357; Part III, Information Science Vol. 9, 43-80.

https://doi.org/10.1016/0020-0255(75)90036-5 https://doi.org/10.1016/0020-0255(75)90017-1

https://doi.org/10.1016/0020-0255(75)90046-8

Zimmermann, H.J. (1991). Fuzzy Set Theory—and Its Application. 2nd Edition, Kluwer Academic Publishers, Boston, MA. https://doi.org/10.1007/978-94-015-7949-0




Copyright (c) 2017 Autor / BY-NC

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.