Using Fuzzy Bio-Inspired Algorithms for Quality Management of Science-Intensive Products

The key way to improve the quality of science-intensive products produced on technological lines that are part of multi-stage production chains is to optimize the design, operation and reengineering of technological processes. High computational complexity, caused by the need to process large volumes of multidimensional data and take into account many time and resource constraints, determines the feasibility of using metaheuristic methods capable of finding close to optimal solutions to algorithmically complex tasks in an acceptable time. The article proposes a new approach to solving tasks of optimizing the composition and operating modes of technological lines, based on the integrated use of swarm intelligence and fuzzy logic. Algorithms inspired by the collective behavior of swimming fish and bacteria were used to solve structural and parametric optimization tasks. Their hybridization with fuzzy logic methods has made it possible to increase the convergence of optimization algorithms by significantly reducing the search space.