Recent Advances on Bioinspired Computation

Bioinspired computation (BIC) has become an emerging and popular part of modern computer science, artificial intelligence, computational intelligence, and evolutionary intelligence.BIC is usually based on biological systems that can be often self-organizing, adaptive, and tolerant of random defects.Most BIC algorithms are mostly swarm intelligence (SI) based, and they mimic the successful characteristics of biological and swarm systems.However, bioinspired computation can be very broad, including swarm intelligence [1-7], membrane [8] and memetic computing, DNA and molecular computing, neural computing, and others.Their applications are also very diverse, including computational intelligence, computational neuroscience, bioinformatics, natural language processing, machine learning, software engineering, scheduling and timetabling, data mining, algorithm theory, and many other areas [9][10][11].Recent advances in this area are relatively extensive, and a special issue can serve as a good summary to provide a snapshot of the recent advances.The responses to our call for papers are overwhelming, and we received nearly two hundred submissions, and after rigorous peer review, only a small fraction of the submissions were accepted for this special issue.This special issue starts with the heterogeneous differential evolution by J. Wang et al., followed by the correction of faulty sensors in phased array radars by J. U. Khan et al.A new variant of harmony search has been proposed to solve binary knapsack problems; then a theoretical model for location of terror response facilities was studied by