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Guerrero, N. M., Aparicio, J., Moragues, R., & Valero-Carreras, D. (2024). Merging Data Envelopment Analysis and Structural Risk Minimization: Some Examples of Use of Multi-output Machine Learning Techniques on Real-World Data. In Analytical Decision Making and Data Envelopment Analysis: Advances and Challenges (pp. 1-32). Singapore: Springer Nature Singapore.

Guerrero, N. M. (Center of Operations Research, Miguel Hernández University of Elche), Aparicio, J. (Center of Operations Research, Miguel Hernández University of Elche), Moragues, R. (Center of Operations Research, Miguel Hernández University of Elche), & Valero-Carreras, D.(Center of Operations Research, Miguel Hernández University of Elche)
Abstract:

Data Envelopment Analysis (DEA) is nowadays a very famous nonparametric […]

By mquesada, ago

Aparicio, J., Esteve, M., & Jin, Q. (2024). Machine Learning Techniques and Efficiency Evaluation: A Survey of Methodological Contributions. Analytical Decision Making and Data Envelopment Analysis: Advances and Challenges, 201-234.

Aparicio, J. (Center of Operations Research, Miguel Hernández University of Elche) , Esteve, M. (Center of Operations Research, Miguel Hernández University of Elche) , & Jin, Q.
Abstract:

This chapter surveys the literature on two types of related contributions. The first group is made up of models devoted to adapting well-known machine learning techniques for estimating […]

By mquesada, ago

Raul Moragues, Juan Aparicio, & Miriam Esteve (2023). An unsupervised learning-based generalization of Data Envelopment Analysis. Operations Research Perspectives, 11, 100284.

Raul Moragues (Operations Research Center, University Miguel Hernández of Elche), Juan Aparicio (Operations Research Center, University Miguel Hernández of Elche) and Miriam Steve (Operations Research Center, University Miguel Hernández of Elche)
Abstract:
In this paper, different upgrading strategies are investigated in the context of the
p-center problem. The possibility of upgrading a set of connections to different centers […]

By anabel.perez, ago

Juan Aparicio, Miriam Esteve, & Magdalena Kapelko (2023). Measuring dynamic inefficiency through machine learning techniques. Expert Systems with Applications, 228, 120417.

Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche; valgrAI – Valencian Graduate School and Research Network of Artificial Intelligence), Miriam Esteve (Center of Operations Research, Miguel Hernandez University of Elche) and Magdalena Kapelko (Department of Logistics. Wrocław University of Economics and Business, Komandorska)
Abstract:
This paper contributes by developing new models for assessing dynamic […]

By anabel.perez, ago

Maria D. Guillen, Juan Aparicio, & Victor J. España (2023). boostingDEA: A boosting approach to Data Envelopment Analysis in R. SoftwareX, 24, 101549.

María D. Guillén (Center of Operations Research, Miguel Hernandez University of Elche), Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche) and Víctor J. España (Center of Operations Research, Miguel Hernandez University of Elche)
Abstract:
boostingDEA is a new package for R that includes functions to estimate production frontiers and make ideal output predictions in […]

By anabel.perez, ago