Development of Methodological Foundations of Logistical Intellectual Control of Complex Systems Based on Hybrid Heuristic Algorithms
Keywords:management of complex systems, heuristic algorithms, hybrid genetic algorithm, neuro-network group method of data handling, theory of fuzzy sets, information technologies
Systematized and generalized existing models of managing the production class of complex distributed systems. A formalized logical-plural model of a complex system is constructed, a description of all its elements is given. A two-level control system for this class of complex systems has been developed. The advantage of the developed system is the possibility of eliminating the existing contradictions between the resource constraints that exist at different structural levels of complex production systems. Elements of a set of control actions based on the principle of hybridization of heuristic algorithms are described. A hybrid genetic algorithm using a fuzzy set machine for a selection operator was used, which was used to optimize the overall logistic transportation plan. Verification of this algorithm was performed both on test functions and on objects of subject domains. The use of the apparatus of fuzzy sets in regulating the dimension of current populations makes it possible, within one formal apparatus, to implement the existing algorithms for selecting suitable individuals for further crossing. A neural-network modification of the method of group accounting of arguments is described as a short-term forecasting model. This model is verified on objects of subject areas, its adequacy and advantages are shown with short-term forecasting of production, financial and statistical indicators.
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