The application of genetic algorithms for organizational systems’ management in case of emergency

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Optimal management of fuel supply system boils down to choosing an energy development strategy which provides consumers with the most efficient and reliable fuel and energy supply. As a part of the program on switching the heat supply distributed management system of the Udmurt Republic to renewable energy sources, an “Information-analytical system of regional alternative fuel supply management” was developed. The paper presents the mathematical model of optimal management of fuel supply logistic system consisting of three interconnected levels: raw material accumulation points, fuel preparation points and fuel consumption points, which are heat sources. In order to increase effective the performance of regional fuel supply system a modification of information-analytical system and extension of its set of functions using the methods of quick responding when emergency occurs are required. Emergencies which occur on any one of these levels demand the management of the whole system to reconfigure. The paper demonstrates models and algorithms of optimal management in case of emergency involving break down of such production links of logistic system as raw material accumulation points and fuel preparation points. In mathematical models, the target criterion is minimization of costs associated with the functioning of logistic system in case of emergency. The implementation of the developed algorithms is based on the usage of genetic optimization algorithms, which made it possible to obtain a more accurate solution in less time. The developed models and algorithms are integrated into the information-analytical system that enables to provide effective management of alternative fuel supply of the Udmurt Republic in case of emergency.

Keywords: genetic algorithm, optimal management, fuel supply, mathematical modeling, alternative energy, emergency
Citation in English: Sairanov A.S., Kasatkina E.V., Nefedov D.G., Rusyak I.G. The application of genetic algorithms for organizational systems’ management in case of emergency // Computer Research and Modeling, 2019, vol. 11, no. 3, pp. 533-556
Citation in English: Sairanov A.S., Kasatkina E.V., Nefedov D.G., Rusyak I.G. The application of genetic algorithms for organizational systems’ management in case of emergency // Computer Research and Modeling, 2019, vol. 11, no. 3, pp. 533-556
DOI: 10.20537/2076-7633-2019-11-3-533-556
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