Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation

Rani, Deepti; Moreira, Maria Madalena

doi:10.1007/s11269-009-9488-0

Cited by 397 publications

(226 citation statements)

References 173 publications

(147 reference statements)

Supporting

Mentioning

210

Contrasting

Unclassified

Order By: Relevance

“…(Wierzbicki et al, 2000): i.e. water resource management and operation (Rani et al, 2010), (Giupponi, 2005), management of complex networks in the urban water cycle (Ocampo et al, 2013), water demand management (Bakker et al, 2013) (Makropoulos et al, 2008), climate change effect on water resources and water supply (Pouget et al, 2012) (Laucelli et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

A decision support system for on-line leakage localization

Meseguer

Mirats-Tur

Cembraño

et al. 2014

Environmental Modelling & Software

View full text Add to dashboard Cite

Abstract:This paper describes a model-driven decision-support system (software tool) implementing a model-based methodology for on-line leakage detection and localization which is useful for a large class of water distribution networks. Since these methods present a certain degree of complexity which limits their use to experts, the proposed software tool focuses on the integration of a method emphasizing its use by water network managers as a decision support system. The proposed software tool integrates a model-based leakage localization methodology based on the use of on-line telemetry information, as well as a water network calibrated hydraulic model. The application of the resulting decision support software tool in a district metered area (DMA) of the Barcelona distribution network is provided and discussed. The obtained results show that the leakage detection and localization may be performed efficiently reducing the required time.

show abstract

Section: Introductionmentioning

confidence: 99%

A decision support system for on-line leakage localization

Meseguer

Mirats-Tur

Cembraño

et al. 2014

Environmental Modelling & Software

View full text Add to dashboard Cite

show abstract

“…The modelling architecture of [4] relies on an adaptive control strategy [33] based on stochastic dynamic programming (SDP), which is widely applied in natural resources management [34][35][36]. Wildfire behaviour dynamics is spatially distributed.…”

Section: Methodsmentioning

confidence: 99%

Dynamic Data Driven Ensemble for Wildfire Behaviour Assessment: A Case Study

Leo

Rigo

Rodriguez-Aseretto

et al. 2013

IFIP Advances in Information and Communication Technology

View full text Add to dashboard Cite

Abstract. Wildfire information has long been collected in Europe, with particular focus on forest fires. The European Forest Fire Information System (EFFIS) of the European Commission complements and harmonises the information collected by member countries and covers the forest fire management cycle. This latter ranges from forest fire preparedness to post-fire impact analysis. However, predicting and simulating fire event dynamics requires the integrated modelling of several sources of uncertainty. Here we present a case study of a novel conceptualization based on a Semantic Array Programming (SemAP) application of the Dynamic Data Driven Application Systems (DDDAS) concept. The case study is based on a new architecture for adaptive and robust modelling of wildfire behaviour. It focuses on the module for simulating wildfire dynamics under fire control scenarios. Rapid assessment of the involved impact due to carbon emission and potential soil erosion is also shown. Uncertainty is assessed by ensembling an array of simulations which consider the uncertainty in meteorology, fuel, software modules. The event under investigation is a major wildfire occurred in 2012, widely reported as one of the worst in the Valencia region, Spain. The inherent data, modelling and software uncertainty are discussed and preliminary results of the robust data-driven ensemble application are presented. The case study suitably illustrates a typical modelling context in many European areas -for which timely collecting accurate local information on vegetation, fuel, humidity, wind fields is not feasible -where robust and flexible approaches may prove as a viable modelling strategy.

show abstract

“…Water resources management widely uses stochastic dynamic programming (SDP) for optimal seasonal allocation of water within reservoirs (as dams or lakes) [58] The growing complexity in forest resources management also increasingly benefits from SDP applications (e.g. fire risk management [59,60]).…”

Section: Uncertainty and Complexity: Semantic Array Programmingmentioning

confidence: 99%

An Architecture for Adaptive Robust Modelling of Wildfire Behaviour under Deep Uncertainty

Rigo

Rodriguez-Aseretto

Bosco

et al. 2013

IFIP Advances in Information and Communication Technology

View full text Add to dashboard Cite

Abstract. Wildfires in Europe -especially in the Mediterranean region -are one of the major treats at landscape scale. While their immediate impact ranges from endangering human life to the destruction of economic assets, other damages exceed the spatio-temporal scale of a fire event. Wildfires involving forest resources are associated with intense carbon emissions and alteration of surrounding ecosystems. The induced land cover degradation has also a potential role in exacerbating soil erosion and shallow landslides. A component of the complexity in assessing fire impacts resides in the difference between uncontrolled wildfires and those for which a control strategy is applied. Robust modelling of wildfire behaviour requires dynamic simulations under an array of multiple fuel models, meteorological disturbances and control strategies for mitigating fire damages. Uncertainty is associated to meteorological forecast and fuel model estimation. Software uncertainty also derives from the datatransformation models needed for predicting the wildfire behaviour and its consequences. The complex and dynamic interactions of these factors define a context of deep uncertainty. Here an architecture for adaptive and robust modelling of wildfire behaviour is proposed, following the semantic array programming paradigm. The mathematical conceptualisation focuses on the dynamic exploitation of updated meteorological information and the design flexibility in adapting to the heterogeneous European conditions. Also, the modelling architecture proposes a multicriteria approach for assessing the potential impact with qualitative rapid assessment methods and more accurate a-posteriori assessment.

show abstract

Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation

Cited by 397 publications

References 173 publications

A decision support system for on-line leakage localization

A decision support system for on-line leakage localization

Dynamic Data Driven Ensemble for Wildfire Behaviour Assessment: A Case Study

An Architecture for Adaptive Robust Modelling of Wildfire Behaviour under Deep Uncertainty

Contact Info

Product

Resources

About