J. J. López-Espín, M. González, J. Aparicio Baeza, D. Giménez, T. El-ghazali
Data Envelopment Analysis (DEA) is a non-parametric methodology for estimating technical efficiency and benchmarking. The mathematical models associated with this principle are based fundamentally on combinatorial NP-hard problems, difficult to be solved. For this reason, this paper uses a parallel matheuristic algorithm, where metaheuristics and exact methods work together to find optimal solutions. Several parallel schemes are used in the algorithm, being possible for them to be configured at different stages of the algorithm. The main intention is to divide the number of problems to be evaluated in equal groups, so that they are resolved in different threads. In addition, taking into account that the main algorithm uses exact methods to solve the mathematical problems, different optimization software has been evaluated to compare their performance when executed in parallel.
Palabras clave / Keywords: metaheuristics, Matheuristic, DEA, parallel computing
Programado
Sesión J05 Heurísticas y Metaheurísticas
31 de mayo de 2018 10:20
Sala 4
