Abstract: An overview concerns topical issues and the current situation regarding cognitive bioinspiral optimization algorithms research. Optimization problems form the majority among the many problems, which are faced by the researchers in the theoretical sphere as well as in the sphere of practical application. For some such problems the solution requires a full search for options. However, the dimensions of these problems are such that the implementation of the search for options is almost impossible  due to  the extremely high time costs. An alternative approach to solving these problems involves the application of methods based on the methodology of cognitive bioinspiral algorithms. When the computer systems became sufficiently fast and inexpensive, the bioengineered algorithms formed an important tool for finding solutions close to optimal solutions for the problems,which were previously been considered insoluble. The methodological and theoretical basis of the survey was found in the provisions of the theory of artificial intelligence and bioinspired computing, decision theory and optimization methods. The review includes a list of world scientific schools and scientists who have made a significant contribution to the development of cognitive bioinspiral algorithms, and also a brief description of the classification, terminology and libraries of bioengineered algorithms. A classical result is presented in the theory of cognitive bioinspiral algorithms - the CPT theorem and the NFL-theorem. The authors provide analysis of regularities, basic elements and structure of cognitive bioinspired calculations, they analyze the issues concerning  representation (coding) of solutions, basic cycle of bioinspired algorithms, extension of cognitive capabilities of operators of bioinspiral algorithms, and drift analysis as a promicing direction in  the sphere of  time of cognitive bioinspiral algorithms analysis.

Abstract: The subject of the article is the current state, problematic issues and promising field of research of bio heuristics for solving optimization problems. Bio heuristics are mathematical transformations of the input stream to the output data based on simulation mechanisms of evolution, natural analogies, on a statistical approach to the study of situations and iterative approximation to the desired solution. Currently, bio heuristics have become an important tool for finding close to optimal solutions of problems which earlier were considered unsolvable. The methodological and theoretical bases of the scoping study are optimization techniques and decision making support methods, artificial intelligence, evolutionary computation theory. The article analyzes the fundamental results obtained in the field of bio-heuristic optimization algorithms: Holland theorem and TAD-theorem. The article establishes patterns and structure of bio heuristics, especially coding solutions, basic cycle of bio heuristics algorithms. The study reviews a promising direction in the analysis time of the biological cognitive heuristics - drift analysis.