A Grid-Based Chameleon Algorithm Based on the Tissue-Like P System with Promoters and Inhibitors

Membrane computing is a novel research branch of bio-inspired computing, which seeks to discover new computational models/framework from biological cells. The obtained computing models are usually called P systems, which are a class of parallel and distributed computing models. In this work, Chameleon algorithm is improved by using grid-based clustering algorithm and parallel evolution mechanism and hierarchical membrane structure in tissue-like P systems with promoters and inhibitors, where promoters and inhibitors are utilized to regulate parallelism of objects evolution. Experiment results show that the proposed algorithm performs well in big cluster analysis. The time complexity is improved to O(n), in comparison with conventional Chameleon algorithm of O(n²). The results give some hints to improve conventional algorithms by using the hierarchical framework and parallel evolution mechanism in membrane computing models.