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

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Dereli T., Ulusam Seçkiner S., Das G. S., Gökçen H., Aydin M. E.

EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING, vol.3, pp.379-423, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Review
  • Volume: 3
  • Publication Date: 2009
  • Doi Number: 10.1504/ejie.2009.027034
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.379-423
  • Keywords: swarm intelligence, public services, ant colony optimisation, ACO, particle swarm optimisation, PSO, bee(s) algorithm, ANT COLONY OPTIMIZATION, MATING OPTIMIZATION, SCHEDULING PROBLEM, SEARCH ALGORITHM, SYSTEMS, DESIGN, POWER, COMBINATORIAL, VARIANTS
  • Gazi University Affiliated: Yes


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.