Abstract
This paper studies the application of a genetic algorithm (GA) for determining closest efficient targets in Data Envelopment Analysis. Traditionally, this problem has been solved in the literature through unsatisfactory methods since all of them are related in some sense to a combinatorial NP-hard problem. This paper presents and studies some algorithms to be used in the creation, crossover and mutation of chromosomes in a GA, in order to obtain an efficient metaheuristic which obtains better solutions.
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Martinez-Moreno, R., Lopez-Espin, J.J., Aparicio, J., Pastor, J.T. (2013). Application of Genetic Algorithms to Determine Closest Targets in Data Envelopment Analysis. In: Omatu, S., Neves, J., Rodriguez, J., Paz Santana, J., Gonzalez, S. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 217. Springer, Cham. https://doi.org/10.1007/978-3-319-00551-5_14
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DOI: https://doi.org/10.1007/978-3-319-00551-5_14
Publisher Name: Springer, Cham
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