Award Price Estimator for Public Procurement Auctions Using Machine Learning Algorithms: Case Study with Tenders from Spain

The public procurement process plays an important role in the efficient use of public resources. In this context, the evaluation of machine learning techniques that are able to predict the award price is a relevant research topic. In this paper, the suitability of a representative set of machine lea...

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Bibliographic Details
Published inStudies in Informatics and Control Vol. 30; no. 4; pp. 67 - 76
Main Authors GARCIA RODRIGUEZ, Manuel J., RODRIGUEZ MONTEQUIN, Vicente, ARANGUREN UBIERNA, Andoni, SANTANA HERMIDA, Roberto, SIERRA ARAUJO, Basilio, ZELAIA JAUREGI, Ana
Format Journal Article
LanguageEnglish
French
Published Bucharest National Institute for Research and Development in Informatics 2021
Subjects
Algorithms
Artificial intelligence
Bids
Case studies
Cost control
Data analysis
Electronic procurement
Machine learning
Neural networks
Regression analysis
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Summary:The public procurement process plays an important role in the efficient use of public resources. In this context, the evaluation of machine learning techniques that are able to predict the award price is a relevant research topic. In this paper, the suitability of a representative set of machine learning algorithms is evaluated for this problem. The traditional regression methods, such as linear regression and random forest, are compared with the less investigated paradigms, such as isotonic regression and popular artificial neural network models. Extensive experiments are conducted based on the Spanish public procurement announcements (tenders) dataset and employ diverse error metrics and implementations in WEKA and Tensorflow 2.
ISSN:1220-1766
1841-429X
DOI:10.24846/v30i4y202106