An heterogeneous particle swarm optimizer with predator and scout particles

  • Authors:

  • Arlindo Silva;Ana Neves;Teresa Gonçalves

  • Affiliations:

  • Escola Superior de Tecnologia, Instituto Politécnico de Castelo Branco, Portugal;Escola Superior de Tecnologia, Instituto Politécnico de Castelo Branco, Portugal;Universidade de Évora, Portugal

  • Venue:
  • AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
  • Year:
  • 2012

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Abstract

We present a new heterogeneous particle swarm optimization algorithm, called scouting predator-prey optimizer. This algorithm uses the swarm's interactions with a predator particle to control the balance between exploration and exploitation. Scout particles are proposed as a straightforward way of introducing new exploratory behaviors into the swarm. These can range from new heuristics that globally improve the algorithm to modifications based on problem specific knowledge. The scouting predator-prey optimizer is compared with several variations of both particle swarm and differential evolution algorithms on a large set of benchmark functions, selected to present the algorithms with different difficulties. The experimental results suggest the new optimizer can outperform the other approaches over most of the benchmark problems.