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Particle swarm optimisation for open shop problems with fuzzy durations

Author:
Palacios Alonso, Juan JoséUniovi authority; González Rodríguez, InésUniovi authority; Rodríguez Vela, María del CaminoUniovi authority; Puente Peinador, JorgeUniovi authority
Publication date:
2011
Editorial:

Springer

Publisher version:
http://dx.doi.org/10.1007/978-3-642-21344-1_38
Descripción física:
p. 362-371
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

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

Description:

4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011, La Palma, Canary Islands, Spain, May 30 - June 3, 2011. Proceedings, Part I

La publicación final está disponible en Springer http://dx.doi.org/10.1007/978-3-642-21344-1_38

URI:
http://hdl.handle.net/10651/7422
ISBN:
978-3-642-21343-4
ISSN:
0302-9743
Identificador local:

20110659

DOI:
10.1007/978-3-642-21344-1_38
Patrocinado por:

This work is supported by the Spanish Ministry of Science and Education under research grant MEC-FEDER TIN2010-20976-C02-02

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