A stochastic programming with imprecise probabilities model for planning water resources systems under multiple uncertainties

Wang, Y. Y.; Huang, Guohe; Wang, Shuo; Li, W.

doi:10.1007/s00477-015-1134-1

Cited by 12 publications

(4 citation statements)

References 36 publications

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“…These uncertainties may stem from inner and outer interactions in water systems, such as variations in technical or commercial parameters cause by technological advances, fluctuations in water requirements cause by changing society and ecological systems, and shifts in water-circulation patterns cause by climate change (Tan et al, 2007(Tan et al, , 2010Chew et al, 2009;Tan et al, 2013;Khor et al, 2014;Bi et al, 2019). Thus, efficient optimization tools for planning industrial park water resource systems under these complexities are desired (Wang et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

A Robust Fractional Model for Improving Industrial Park Water Use Efficiency Under Dual Uncertainties

Lan

Wang

Tan

et al. 2022

Preprint

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As an existing form of high aggregation of industries, industrial parks, have problems with a large demand for water and sewage discharge. Therefore, developing an effective approach to improve the efficiency of industrial park water use is urgently needed. Originating from internal and external changes, complicated uncertainties may coexist in multiple system components and their correlations within industrial park water resource management. Previous studies ignored the uncertain probability related to water inflow, which is difficult to estimate for long-term decision-making problems. This research describes the exploitation of an inexact two-stage stochastic partial fractional programming (ITSPF) method for sustainable industrial park water supply, under dual uncertainties. ITSPF is developed via the synthesis of linear partial information, interval programming, two-stage stochastic programming, and fractional programming techniques. It could improve conventional industrial park water resource optimization by solving the uncertain probability of water inflow levels while optimizing the ratio issues. The results show that various water allocation plans within different inflow level probabilities can be generated by handling the trade-off between water consumption and system benefit. And the amount of reclaimed water would be increased under the higher risk of water shortage. The comparisons of ITSPF results against the least-cost model and model with deterministic probability of water inflow levels demonstrated that ITSPF could not only result in higher resource-use efficiency, but also avoid missing possible solution sets and offer a pragmatic way for obtaining satisfactory alternatives by providing wider adjustable ranges.

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Section: Introductionmentioning

confidence: 99%

A Robust Fractional Model for Improving Industrial Park Water Use Efficiency Under Dual Uncertainties

Lan

Wang

Tan

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The above complexities bring great challenges for water managers in decision making. Therefore, suitable and effective optimization tools are desired to help decision makers to identify the optimal water allocation strategies in such complex conditions [2].…”

Section: Introductionmentioning

confidence: 99%

Inexact Two-Stage Stochastic Programming for Water Resources Allocation under Considering Demand Uncertainties and Response—A Case Study of Tianjin, China

Sun

Ma³

et al. 2017

Water

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Abstract:In this paper, an inexact two-stage stochastic programming model was developed for supporting regional water resource allocation management under uncertainties. The proposed model is an integrated framework of interval parameter programming and two-stage stochastic programming, which can tackle uncertain parameters expressed as interval values with probability distribution information. The proposed model was successfully applied to a typical heavy industrial city suffering water shortage in the east of China, Tianjin. The uncertainties of future water demand were taken into account through generating a set of representative scenarios. The results indicated that different scenarios would affect the water distribution patterns, water shortages, total benefits and system cost. The results revealed that the transferred water from Luan River and Changjiang River would still be the main water resource for each water user. Besides, nearly all water demand in planning horizon would be guaranteed through the reasonable dispatch except under high demand level scenario, in which a small proportion of water requirement in agricultural, municipal and environmental sectors would not be satisfied. The developed method could be used by environmental managers to identify the optimal water supply plan from multiple sources to different end-user sectors under system uncertainties.

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“…The randomness of available water amount and the imprecision of socio-economic data usually confused water managers before the interval two-stage stochastic programming (ITSP) had been developed. ITSP is an effective model for handling uncertainties expressed as imprecise parameters with known upper and lower bounds as well as random variables with known probability distributions [22]. Moreover, uncertainties in many practical allocation problems were expressed as fuzzy sets, which called for effective methods to facilitate communicating fuzzy uncertainties into the optimization process.…”

Section: Introductionmentioning

confidence: 99%

A Regional Water Optimal Allocation Model Based on the Cobb-Douglas Production Function under Multiple Uncertainties

Zhang¹,

Tan²,

Zhang³

et al. 2017

Water

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Abstract:To optimize the water distribution of three industries based on the water demand prediction under multiple uncertainties, a fuzzy credibility-constrained interval two-stage stochastic programming (FCITSP) model base on the Cobb-Douglas production (CD) function was developed. The CD-FCITSP model integrated fuzzy credibility-constrained programming (FCP), an interval two-stage stochastic programming (ITSP) method and CD function. The developed model could deal with uncertainties with interval, random, and fuzzy features, reflect tradeoffs between different water use sectors, and provide water managers in arid regions with sustainable and reasonable water-allocation schemes under different credibility scenarios of local policies. Moreover, the relationships between economic benefits and water consumption were taken into consideration via the Cobb-Douglas production function. The developed model was applied to support the optimal allocation of limited water resources in Minqin County, northwest China. The obtained solution demonstrated that the developed method could help local water managers to effectively allocate limited water under multiple uncertainties and different credibility scenarios. In addition, water use efficiency could be promoted and the emissions of major pollutants could be reduced. The developed method could be extended to water management practices in other arid regions.

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A stochastic programming with imprecise probabilities model for planning water resources systems under multiple uncertainties

Cited by 12 publications

References 36 publications

A Robust Fractional Model for Improving Industrial Park Water Use Efficiency Under Dual Uncertainties

A Robust Fractional Model for Improving Industrial Park Water Use Efficiency Under Dual Uncertainties

Inexact Two-Stage Stochastic Programming for Water Resources Allocation under Considering Demand Uncertainties and Response—A Case Study of Tianjin, China

A Regional Water Optimal Allocation Model Based on the Cobb-Douglas Production Function under Multiple Uncertainties

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