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Artificial Intelligence and Decision Making, 2017, Issue 1, Pages 84–97
(Mi iipr239)
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This article is cited in 3 scientific papers (total in 3 papers)
Decision-making
Decision support for strategic decision making on water supply of the Lower Volga River based on Pareto frontier visualization
M. V. Bolgova, A. L. Buberb, A. V. Lotovc a Water Problems Institute of the Russian Academy of Sciences, Moscow
b All-Russia Research Institute of Hydraulic Engineering and Land Reclamation of A.N. Kostyakov, Moscow
c Dorodnitsyn Computing Centre of the Russian Academy of Sciences, Moscow
Abstract:
The paper describes application of visualization of the Pareto frontier in the process of decision making in the framework of the methodology for integrated assessment of environmental problems. Integrated assessment is applied in supporting the choice of long-term strategic decisions on water management of the River Volga while a special attention is given to the problems of environmental sustainability and economic development of the Volga-Akhtuba floodplain. The methodology is outlined, the decision problem is formulated and the integrated mathematical model is described, which provides an opportunity to estimate the reliability of meeting of mutually contradicting requirements to water management. It is shown that application of the Pareto frontier visualization is an effective tool for supporting the decision making on feasible strategic goal for the Volga-Kama reservoir cascade control.
Keywords:
decision support, multi-objective optimization, Pareto frontier visualization, integrated assessment of environmental problems, Volga-Akhtuba floodplain.
Citation:
M. V. Bolgov, A. L. Buber, A. V. Lotov, “Decision support for strategic decision making on water supply of the Lower Volga River based on Pareto frontier visualization”, Artificial Intelligence and Decision Making, 2017, no. 1, 84–97; Scientific and Technical Information Processing, 45:5 (2018), 297–306
Linking options:
https://www.mathnet.ru/eng/iipr239 https://www.mathnet.ru/eng/iipr/y2017/i1/p84
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