Particle swarm optimisation for open shop problems with fuzzy durations

Authors:
Juan José Palacios;Inés González-Rodríguez;Camino R. Vela;Jorge Puente
Affiliations:
A.I. Centre and Department of Computer Science, University of Oviedo, Spain;Department of Mathematics, Statistics and Computing, University of Cantabria, 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
Venue:
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Year:
2011

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Abstract

In this paper we confront 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 particle swarm optimization (PSO) approach to minimise the expected makespan using priorities to represent particle position, as well as a decoding algorithm to generate schedules in a subset of possibly active ones. Finally, the performance of the PSO is tested on several benchmark problems, modified so as to have fuzzy durations, compared with a memetic algorithm from the literature.