Bio-inspired computing methods take inspiration from nature to develop optimization and search algorithms or metaheuristics, typically in order to tackle the search of optimal solutions of complex problems in science and engineering, which usually imply a high dimensionality of the search space.

Apart from the traditional evolutionary computing methods, artificial immune systems, ant algorithms or particle swarm optimization, the session is intended to focus on new bio-inspired solutions such as swarm algorithm solutions based on bee colonies, algorithms based on firefly insect behavior, artificial algae algorithm and many more, together with their combination with local search strategies or other metaheuristics. The researchers in this field must be self-critical with the boom of such new solutions, contrasting what is new and what is included in other traditional search algorithms or what novelty is provided in a new bio-inspired metaheuristic. Besides, the proposals should be competitive with other methods in the state of the art.

The aim is that the session provides a meeting point for IWINAC attendees and researchers who have a current or developing interest in bioinspired approaches and their applications.

Topics areas are include(but not restricted to):

  • Bio-inspired approaches based on animal behavior (Cuckoo search, Cat swarm, Artificial Bee Colony, Bat algorithm, Wolf search, …).
  • Bio-inspired approaches based on plant behavior (artificial algae algorithm, flower pollination algorithm, PIBO, …).
  • Bio-inspired approaches based on bacteria like BFO.
  • New approaches in evolutionary computing methods.
  • Combination of bio-inspired approaches with local search: Lamarckian strategies, Baldwinian strategies, memetic algorithms.
  • Combination of the bio-inspired approaches with artificial life models like cellular automata or Lindenmayer systems.
  • Applications with bio-inspired approaches.