Multiobjective optimisation on a budget: Exploring surrogate modelling for robust multi-reservoir rules generation under hydrological uncertainty

I. Tsoukalas, and C. Makropoulos, Multiobjective optimisation on a budget: Exploring surrogate modelling for robust multi-reservoir rules generation under hydrological uncertainty, Environmental Modelling and Software, 69, 396–413, doi:10.1016/j.envsoft.2014.09.023, 2015.

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[English]

Developing long term operation rules for multi-reservoir systems is complicated due to the number of decision variables, the non-linearity of system dynamics and the hydrological uncertainty. This uncertainty can be addressed by coupling simulation models with multi-objective optimisation algorithms driven by stochastically generated hydrological timeseries but the computational effort required imposes barriers to the exploration of the solution space. The paper addresses this by (a) employing a parsimonious multi-objective parameterization-simulation-optimization (PSO) framework, which incorporates hydrological uncertainty through stochastic simulation and allows the use of probabilistic objective functions and (b) by investigating the potential of multi-objective surrogate based optimisation (MOSBO) to significantly reduce the resulting computational effort. Three MOSBO algorithms are compared against two multi-objective evolutionary algorithms. Results suggest that MOSBOs are indeed able to provide robust, uncertainty-aware operation rules much faster, without significant loss of neither the generality of evolutionary algorithms nor of the knowledge embedded in domain-specific models.

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Our works that reference this work:

1. I. Tsoukalas, and C. Makropoulos, A surrogate based optimization approach for the development of uncertainty-aware reservoir operational rules: the case of Nestos hydrosystem, Water Resources Management, 29 (13), 4719–4734, doi:10.1007/s11269-015-1086-8, 2015.
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Other works that reference this work (this list might be obsolete):

1. Müller, R., and N. Schütze, Multi-objective optimization of multi-purpose multi-reservoir systems under high reliability constraints, Environmental Earth Sciences, 75:1278, doi:10.1007/s12665-016-6076-5, 2016.
2. Christelis, V., and A. G. Hughes, Metamodel-assisted analysis of an integrated model composition: an example using linked surface water – groundwater models, Environmental Modelling and Software, doi:10.1016/j.envsoft.2018.05.004, 2018.
3. Christelis, V., G. Kopsiaftis, and A. Mantoglou, Performance comparison of multiple and single surrogate models for pumping optimization of coastal aquifers, Hydrological Sciences Journal, doi:10.1080/02626667.2019.1584400, 2019.

Tagged under: Hydrosystems, Optimization