Optimal Allocation of Water Resources Using a Two-Stage Stochastic Programming Method with Interval and Fuzzy Parameters

Khosrojerdi, Tooraj; Moosavirad, Seyed Hamed; Ariafar, Shahram; Ghaeini-Hessaroeyeh, Mahnaz

doi:10.1007/s11053-018-9440-1

Cited by 27 publications

(10 citation statements)

References 39 publications

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“…The model target value and fuzzy membership would vary within their intervals as the parameters in the IPFTSP model are adjusted within the interval [ 29 ]. Clarifying the changing relationship between the model target value and fuzzy membership assists the decision-makers to make the preferred decision.…”

Section: Resultsmentioning

confidence: 99%

“…Another example is the two-stage mixed-integer fuzzy programming method with an interval-valued membership function proposed by Wang et al for resolving the flood diversion planning problem under uncertainties [ 27 ]. Miao et al proposed an interval-fuzzy de novo programming method for allocating water resources under uncertainties [ 28 ], while Khosrojerdi et al suggested a two-stage interval-parameter stochastic fuzzy programming method to optimally allocate water resources to different users under uncertainties [ 29 ]. These examples show that the FMP method can effectively address fuzzy uncertainties in resource management systems [ 30 , 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Ecological Water Supplement Scheme for Improved Suitable Habitat Area for Rare Migratory Birds in Nature Reserves Using Interval-Parameter Fuzzy Two-Stage Stochastic Programming Model

Liao

Meng

Ren

et al. 2020

IJERPH

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The optimization of ecological water supplement scheme in Momoge National Nature Reserve (MNNR), using an interval-parameter two-stage stochastic programming model (IPTSP), still experiences problems with fuzzy uncertainties and the wide scope of the obtained optimization schemes. These two limitations pose a high risk of system failure causing high decision risk for decision-makers and render it difficult to further undertake optimization schemes respectively. Therefore, an interval-parameter fuzzy two-stage stochastic programming (IPFTSP) model derived from an IPTSP model was constructed to address the random variable, the interval uncertainties and the fuzzy uncertainties in the water management system in the present study, to reduce decision risk and narrow down the scope of the optimization schemes. The constructed IPFTSP model was subsequently applied to the optimization of the ecological water supplement scheme of MNNR under different scenarios, to maximize the recovered habitat area and the carrying capacity for rare migratory water birds. As per the results of the IPFTSP model, the recovered habitat areas for rare migratory birds under low, medium and high flood flow scenarios were (14.06, 17.88) × 103, (14.92, 18.96) × 103 and (15.83, 19.43) × 103 ha, respectively, and the target value was (14.60, 18.47) × 103 ha with a fuzzy membership of (0.01, 0.83). Fuzzy membership reflects the possibility level that the model solutions satisfy the target value and the corresponding decision risk. We further observed that the habitat area recovered by the optimization schemes of the IPFTSP model was significantly increased compared to the recommended scheme, and the increases observed were (5.22%, 33.78%), (11.62%, 41.88%) and (18.44%, 45.39%). In addition, the interval widths of the recovered habitat areas in the IPFTSP model were reduced by 17.15%, 17.98% and 23.86%, in comparison to those from the IPTSP model. It was revealed that the IPFTSP model, besides generating the optimal decision schemes under different scenarios for decision-makers to select and providing decision space to adjust the decision schemes, also shortened the decision range, thereby reducing the decision risk and the difficulty of undertaking decision schemes. In addition, the fuzzy membership obtained from the IPFTSP model, reflecting the relationship among the possibility level, the target value, and the decision risk, assists the decision-makers in planning the ecological water supplement scheme with a preference for target value and decision risk.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Ecological Water Supplement Scheme for Improved Suitable Habitat Area for Rare Migratory Birds in Nature Reserves Using Interval-Parameter Fuzzy Two-Stage Stochastic Programming Model

Liao

Meng

Ren

et al. 2020

IJERPH

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“…To increase the reliability of water supply, different water resource allocations were examined to negotiate a compromise between hydropower generation and water supply. Numerous studies exist and various systems analysis models have been applied to solve multi-purpose optimization problems [6][7][8][9][10][11][12]. In general, these models can be classified as simulation models, optimization models, and the combination of simulation and optimization models [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Management Strategies of a Multi-Purpose Multi-Reservoir System in Vietnam

Chou

Linh

2020

Water

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Resource shortages are having an increasingly severe impact as global trends like rapid population growth, urbanization, economic development, and climate change unfold. Moreover, rising living standards across many regions are also affecting water and energy resources. This entails an urgent requirement to improve water resources management. An important improvement is to transfer water between the different uses of the reservoir system. A compromise between the needs of hydropower generation and the water supply can be negotiated for the reservoir system to reduce the severity of water shortages. The Be River basin in Vietnam was selected as a case study to investigate. The combination of the generalized water allocation simulation model (GWASIM) and the bounded optimization by quadratic approximation (BOBYQA) algorithm was applied to optimize hydropower generation in various water shortage scenarios. The results present optimized hydropower generation policies for cascade reservoirs that would significantly improve the present operating policy in terms of both the water supply and hydropower generation. Moreover, multiple scenarios will provide flexibility to the reservoir operator by giving the relationship between water and energy. Given water supply conditions, the operator will be able to choose among several optimal solutions to ensure greater water resource efficiency in the Be River basin.

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“…Previously, two-stage stochastic programming (TSP) was reported as an effective tool for water resources planning under uncertainty [9][10][11][12][13][14][15][16][17][18]. The TSP methods reported are characterized by two essential features: the uncertainty (i.e., random river flows) is but not only expressed with a certain probabilistic distribution and the sequence of decisions.…”

Section: Introductionmentioning

confidence: 99%

“…The research handled the uncertainties of future water demand through generating a set of representative scenarios and analyzed different scenarios to discuss their effects on the water distribution patterns, water shortages, total benefits, and system cost. Khosrojerdi, T. et al [18] developed optimal allocation strategies of water resources using a TSP method with interval and fuzzy parameters. In the abovementioned TSP approaches, the total expected value of the second-stage costs (e.g., economic penalties or recourse costs) is measured without considering and controlling the variabilities of the costs under different possible water-delivery scenarios.…”

Section: Introductionmentioning

confidence: 99%

Risk Aversion Based Inexact Stochastic Dynamic Programming Approach for Water Resources Management Planning under Uncertainty

et al. 2019

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In this study, a dual interval robust stochastic dynamic programming (DIRSDP) method is developed for planning water resources management systems under uncertainty. As an extension of the existing interval stochastic dynamic programming (ISDP) method, DIRSDP can deal with two-stage stochastic programming (TSP)-based planning problems associated with dynamic features, input uncertainties, and multistage concerns. Compared with other optimization methods dealing with uncertainties, the developed DIRSDP method has advantages in addressing uncertainties with complex presentations and reflecting decision makers’ risk-aversion attitudes within its optimization process. Parameters in the DIRSDP model can be represented as probability distributions as well as single and/or dual intervals. Decision makers’ risk-aversion attitudes can be reflected through restricting the deviation of the recourse costs to a tolerance level. Water-allocation plans can then be developed based on the analysis of tradeoffs between the system benefit and solution robustness. The developed method is applied to a case of water resources management planning. The solutions are reasonable, indicating applicability of the developed methodology.

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Optimal Allocation of Water Resources Using a Two-Stage Stochastic Programming Method with Interval and Fuzzy Parameters

Cited by 27 publications

References 39 publications

Optimization of Ecological Water Supplement Scheme for Improved Suitable Habitat Area for Rare Migratory Birds in Nature Reserves Using Interval-Parameter Fuzzy Two-Stage Stochastic Programming Model

Optimization of Ecological Water Supplement Scheme for Improved Suitable Habitat Area for Rare Migratory Birds in Nature Reserves Using Interval-Parameter Fuzzy Two-Stage Stochastic Programming Model

Optimizing the Management Strategies of a Multi-Purpose Multi-Reservoir System in Vietnam

Risk Aversion Based Inexact Stochastic Dynamic Programming Approach for Water Resources Management Planning under Uncertainty

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