Abstract
This article discusses the results of solving the problems of complex objects (CO) recovery programs, which are based on the structure dynamics management and control of these objects. The main advantage is the combined use of different models, methods and algorithms (analytical, simulation, logical-algebraic and their combinations) which allows to compensate their objectively existing shortcomings and limitations while enhancing their positive qualities during planning and scheduling for CO proactive intellectual situational management and control in emergencies. Proposed integration of CO management and control methods allows to link at the constructive level the substantive and formal aspects of the solving problem. Within the framework of the presented methodology, it is possible to rely on the fundamental scientific results obtained to date in the modern control theory of complex dynamic systems and knowledge engineering with a tunable structure during the situational management of complex objects recovery. It allows to determine the sequence of tasks and operations (to synthesize CO disaster recovery plans and schedules), to find and reasonably choose compromise solutions in the presence of several options for the sequence of operations. The developed CO disaster recovery plans and schedules are evaluated by involving experts and identifying their implicit expertise with the help of multicriteria approach. The problem statement of recovery is given. The new method of multicriteria evaluation of the CO disaster recovery plans and schedules, based on a combination of theory of experiments design models and models of fuzzy rule-based language is given.
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Sokolov, B., Pavlov, A., Potriasaev, S., Zakharov, V. (2020). Methodology and Technologies of the Complex Objects Proactive Intellectual Situational Management and Control in Emergencies. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_24
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