A Genetic Algorithm for the Open Shop Problem with Uncertain Durations

Authors:
Juan José Palacios;Jorge Puente;Camino R. Vela;Inés González-Rodríguez
Affiliations:
A.I. Centre and Department of Computer Science, University of Oviedo, Spain;A.I. Centre and Department of Computer Science, University of Oviedo, Spain;A.I. Centre and Department of Computer Science, University of Oviedo, Spain;Department of Mathematics, Statistics and Computing, University of Cantabria, Spain
Venue:
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Year:
2009

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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.