Title: An exploration of the literature on the use of 'swarm intelligence-based techniques' for public service problems

Authors: Turkay Dereli, Serap Ulusam Seckiner, Gulesin Sena Das, Hadi Gokcen, Mehmet Emin Aydin

Addresses: Department of Industrial Engineering, Faculty of Engineering, University of Gaziantep, 27310 Sehitkamil, Gaziantep, Turkey. ' Department of Industrial Engineering, Faculty of Engineering, University of Gaziantep, 27310 Sehitkamil, Gaziantep, Turkey. ' TUBITAK, The Scientific and Technological Research Council of Turkey, EU Framework Programs National Office, Tunus Caddesi No. 80, Kavaklıdere Ankara 06100, Turkey. ' Department of Industrial Engineering, Faculty of Engineering and Architecture, Gazi University, Maltepe, Ankara 06570, Turkey. ' Department of Computing and Information Systems, University of Bedfordshire, Institute for Research in Applicable Computing, Park Square, Luton, Bedforshire, LU1 3JU, UK

Abstract: The importance of studying public service systems and finding robust solutions to the problems encountered in public service management has increased considerably over the past decade. One of the main objectives is to find acceptable solutions to Public Service Problems (PSPs) within an affordable period of time. However, many PSPs remain difficult to solve within a reasonable time due to their complexity and dynamic nature. This requires solving PSPs with techniques which provide efficient algorithmic solutions. There has been increasing attention in the literature to solving PSPs through the use of Swarm Intelligence-Based Techniques (SIBTs) like ant colony optimisation, particle swarm optimisation, Bee(s) Algorithm (BA), etc. This paper presents a review of Swarm Intelligence (SI) applications in public services (including PSPs in specific application areas), as well as the models and SI algorithms that have been reported in the literature. [Received 30 January 2008; Revised 4 December 2008; Revised 17 March 2009; Accepted 23 March 2009]

Keywords: swarm intelligence; public services; ant colony optimisation; ACO; particle swarm optimisation; PSO; bees algorithm; public service management.

DOI: 10.1504/EJIE.2009.027034

European Journal of Industrial Engineering, 2009 Vol.3 No.4, pp.379 - 423

Published online: 13 Jul 2009 *

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