The search for biologically plausible ideas, models and computational paradigms always drew the interest of computer scientists, particularly those from the natural computing area. Also, the concept of optimisation can be abstracted from several natural processes, for instance, in the evolution of species, in the behaviour of social groups, in the dynamics of the immune system, in the food search strategies and in the ecological relationships of different animal populations. Hence, this work highlights the main properties of ecosystems that can be important for building computational tools to solve complex problems. Also, we introduce computational descriptions for such biologically plausible functionalities (e.g., habitats, ecological relationships, ecological succession, and another). The main differential of the discussion presented in this paper is the cooperative use of different populations (candidate solutions) that co-evolve in an ecological context. In addition to the use of different search strategies cooperatively, this work opens the possibility of inserting ecological concepts in the optimisation process allowing the development of new bio-plausible hybrid systems. The potentiality of some ecological concepts is also presented in a simplified ecology-inspired algorithm for optimisation. Finally, concluding remarks and ideas for future research are presented.
['Rafael Stubs Parpinelli', 'Heitor S. Lopes']
Biological plausibility in optimisation: an ecosystemic view