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A genetic algorithm for the open shop problem with uncertain durations

Author:
Palacios Alonso, Juan JoséUniovi authority; Puente Peinador, JorgeUniovi authority; Rodríguez Vela, María del CaminoUniovi authority; González Rodríguez, InésUniovi authority
Publication date:
2009
Editorial:

Springer

Publisher version:
http://dx.doi.org/10.1007/978-3-642-02264-7_27
Citación:
Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira’s Scientific Legacy, p. 255-264 (2009); doi:10.1007/978-3-642-02264-7_27
Serie:

Lecture Notes in Computer Science;5601

Descripción física:
p. 255-264
Abstract:

We consider a variation of the open shop problem where task durations are allowed to be uncertain and where uncertainty is modelled using fuzzy numbers. We propose a genetic approach to minimise the expected makespan: we consider different possibilities for the genetic operators and analyse their performance, in order to obtain a competitive configuration. Finally, the performance of the proposed genetic algorithm is tested on several benchmark problems, modified so as to have fuzzy durations, compared with a greedy heuristic from the literature

We consider a variation of the open shop problem where task durations are allowed to be uncertain and where uncertainty is modelled using fuzzy numbers. We propose a genetic approach to minimise the expected makespan: we consider different possibilities for the genetic operators and analyse their performance, in order to obtain a competitive configuration. Finally, the performance of the proposed genetic algorithm is tested on several benchmark problems, modified so as to have fuzzy durations, compared with a greedy heuristic from the literature

Description:

Third International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2009 (3rd. 2009. Santiago de Compostela, Spain)

URI:
http://hdl.handle.net/10651/11563
ISBN:
9783642022630
ISSN:
0302-9743
Identificador local:

20090157

DOI:
10.1007/978-3-642-02264-7_27
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