FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3157992068> ?p ?o ?g. }

• W3157992068 endingPage "103816" @default.
• W3157992068 startingPage "103816" @default.
• W3157992068 abstract "In this research, a dual-randomness bi-level interval multi-objective programming (DR-BIMP) model was developed for supporting water resources management among multiple water sectors under complexities and uncertainties. Techniques of bi-level multi-objective programming (BMOP), double-sided stochastic chance-constrained programming (DSCCP), and interval parameter programming (IPP) were incorporated into an integrated modeling framework to achieve comprehensive consideration of the complexities and uncertainties of water resources management systems. The DR-BIMP model can not only effectively deal with the interactive effects between multiple decision-makers in complex water management systems through the bi-level hierarchical strategies, but also can characterize the multiple uncertainties information expressed as interval format and probability density functions. It could thus improve upon the existing bi-level multi-objective programming through addressing discrete interval parameters and dual-randomness problems in optimization processes simultaneously. Then, the developed model was applied to a real-world case to optimally allocate water resources among three different water sectors in five sub-regions in the Dongjiang River basin, south China. The results of the model include determining values, interval values, and stochastic distribution information, which can assist bi-level decision-makers to plan future resources effectively to some extent. After comparing the variations of results, it is found that an increasing probability level can lead to higher system benefits, which is increased from [20,786.00, 26,425.92] × 108 CNY to [22,290.84, 27,492.57] × 108 CNY, while the Gini value is reduced from [0.365, 0.446] to [0.345, 0.405]. A set of increased probability levels gives rise to the lower-level objectives. Furthermore, the advantages of the DR-BIMP model were highlighted by comparing with the other models originated from the developed model. The comparison results indicated that the DR-BIMP model was a valuable tool for generating a range of decision alternatives and thus assists the bi-level decision-makers to identify the desired water resources allocation schemes under multiple scenarios." @default.
• W3157992068 created "2021-05-10" @default.
• W3157992068 creator A5005810257 @default.
• W3157992068 creator A5009971655 @default.
• W3157992068 creator A5019860038 @default.
• W3157992068 creator A5022098030 @default.
• W3157992068 creator A5041643505 @default.
• W3157992068 date "2021-08-01" @default.
• W3157992068 modified "2023-10-18" @default.
• W3157992068 title "A dual-randomness bi-level interval multi-objective programming model for regional water resources management" @default.
• W3157992068 cites W1577259809 @default.
• W3157992068 cites W1966291122 @default.
• W3157992068 cites W1967029857 @default.
• W3157992068 cites W1981090512 @default.
• W3157992068 cites W1994956670 @default.
• W3157992068 cites W1995134127 @default.
• W3157992068 cites W2020284580 @default.
• W3157992068 cites W2044078351 @default.
• W3157992068 cites W2054252874 @default.
• W3157992068 cites W2090485323 @default.
• W3157992068 cites W2112055273 @default.
• W3157992068 cites W2113567362 @default.
• W3157992068 cites W2227885554 @default.
• W3157992068 cites W2288120200 @default.
• W3157992068 cites W2294551335 @default.
• W3157992068 cites W2600799528 @default.
• W3157992068 cites W2659313031 @default.
• W3157992068 cites W2724523201 @default.
• W3157992068 cites W2731535391 @default.
• W3157992068 cites W2748680855 @default.
• W3157992068 cites W2758440947 @default.
• W3157992068 cites W2766928469 @default.
• W3157992068 cites W2769618727 @default.
• W3157992068 cites W2772933110 @default.
• W3157992068 cites W2776642731 @default.
• W3157992068 cites W2782343704 @default.
• W3157992068 cites W2789349114 @default.
• W3157992068 cites W2792024545 @default.
• W3157992068 cites W2792030076 @default.
• W3157992068 cites W2883182214 @default.
• W3157992068 cites W2884312492 @default.
• W3157992068 cites W2887716761 @default.
• W3157992068 cites W2889950163 @default.
• W3157992068 cites W2890612291 @default.
• W3157992068 cites W2900280201 @default.
• W3157992068 cites W2900827342 @default.
• W3157992068 cites W2902336242 @default.
• W3157992068 cites W2905394838 @default.
• W3157992068 cites W2923779232 @default.
• W3157992068 cites W2925301629 @default.
• W3157992068 cites W2965998738 @default.
• W3157992068 cites W2966066892 @default.
• W3157992068 cites W3001286735 @default.
• W3157992068 cites W3045412366 @default.
• W3157992068 cites W3045619837 @default.
• W3157992068 cites W4236427546 @default.
• W3157992068 cites W857483607 @default.
• W3157992068 doi "https://doi.org/10.1016/j.jconhyd.2021.103816" @default.
• W3157992068 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33965809" @default.
• W3157992068 hasPublicationYear "2021" @default.
• W3157992068 type Work @default.
• W3157992068 sameAs 3157992068 @default.
• W3157992068 citedByCount "4" @default.
• W3157992068 countsByYear W31579920682022 @default.
• W3157992068 countsByYear W31579920682023 @default.
• W3157992068 crossrefType "journal-article" @default.
• W3157992068 hasAuthorship W3157992068A5005810257 @default.
• W3157992068 hasAuthorship W3157992068A5009971655 @default.
• W3157992068 hasAuthorship W3157992068A5019860038 @default.
• W3157992068 hasAuthorship W3157992068A5022098030 @default.
• W3157992068 hasAuthorship W3157992068A5041643505 @default.
• W3157992068 hasConcept C105795698 @default.
• W3157992068 hasConcept C114614502 @default.
• W3157992068 hasConcept C124952713 @default.
• W3157992068 hasConcept C125112378 @default.
• W3157992068 hasConcept C126255220 @default.
• W3157992068 hasConcept C137631369 @default.
• W3157992068 hasConcept C142362112 @default.
• W3157992068 hasConcept C149441793 @default.
• W3157992068 hasConcept C153823671 @default.
• W3157992068 hasConcept C18903297 @default.
• W3157992068 hasConcept C2778067643 @default.
• W3157992068 hasConcept C2780980858 @default.
• W3157992068 hasConcept C33923547 @default.
• W3157992068 hasConcept C41008148 @default.
• W3157992068 hasConcept C41045048 @default.
• W3157992068 hasConcept C42475967 @default.
• W3157992068 hasConcept C61157135 @default.
• W3157992068 hasConcept C86803240 @default.
• W3157992068 hasConceptScore W3157992068C105795698 @default.
• W3157992068 hasConceptScore W3157992068C114614502 @default.
• W3157992068 hasConceptScore W3157992068C124952713 @default.
• W3157992068 hasConceptScore W3157992068C125112378 @default.
• W3157992068 hasConceptScore W3157992068C126255220 @default.
• W3157992068 hasConceptScore W3157992068C137631369 @default.
• W3157992068 hasConceptScore W3157992068C142362112 @default.
• W3157992068 hasConceptScore W3157992068C149441793 @default.
• W3157992068 hasConceptScore W3157992068C153823671 @default.

• next