A Multi-criteria Decision-making Optimization Model for Flood Management in Reservoirs

Nematollahi, Banafsheh; Nikoo, Mohammad Reza; Gandomi, Amir H.; Talebbeydokhti, Nasser; Rakhshandehroo, Gholamreza

doi:10.1007/s11269-022-03284-0

Cited by 14 publications

(6 citation statements)

References 32 publications

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“…The Particle Swarm Optimization (PSO) method was used in five articles (12.2%) [28,77,80,89,90]. The reasons for selecting the PSO method were its key features, like its requirement for fewer parameters, easy operation, fast convergence, better global optimization capability, and high search speed even for a complex model [28,90].…”

Section: Multi-objective Optimization (Moo) Methodsmentioning

confidence: 99%

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Development of a Generic Decision Tree for the Integration of Multi-Criteria Decision-Making (MCDM) and Multi-Objective Optimization (MOO) Methods under Uncertainty to Facilitate Sustainability Assessment: A Methodical Review

Ferdous,

Bensebaa,

Milani

et al. 2024

Sustainability

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The integration of Multi-Objective Optimization (MOO) and Multi-Criteria Decision-Making (MCDM) has gathered significant attention across various scientific research domains to facilitate integrated sustainability assessment. Recently, there has been a growing interest in hybrid approaches that combine MCDM with MOO, aiming to enhance the efficacy of the final decisions. However, a critical gap exists in terms of providing clear methodological guidance, particularly when dealing with data uncertainties. To address this gap, this systematic review is designed to develop a generic decision tree that serves as a practical roadmap for practitioners seeking to perform MOO and MCDM in an integrated fashion, with a specific focus on accounting for uncertainties. The systematic review identified the recent studies that conducted both MOO and MCDM in an integrated way. It is important to note that this review does not aim to identify the superior MOO or MCDM methods, but rather it delves into the strategies for integrating these two common methodologies. The prevalent MOO methods used in the reviewed articles were evolution-based metaheuristic methods. TOPSIS and PROMETHEE II are the prevalent MCDM ranking methods. The integration of MOO and MCDM methods can occur either a priori, a posteriori, or through a combination of both, each offering distinct advantages and drawbacks. The developed decision tree illustrated all three paths and integrated uncertainty considerations in each path. Finally, a real-world case study for the pulse fractionation process in Canada is used as a basis for demonstrating the various pathways presented in the decision tree and their application in identifying the optimized processing pathways for sustainably obtaining pulse protein. This study will help practitioners in different research domains use MOO and MCDM methods in an integrated way to identify the most sustainable and optimized system.

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Section: Multi-objective Optimization (Moo) Methodsmentioning

confidence: 99%

“…This type of comprehensive weighting method is more effective and stable [97]. Only a few studies were dependent on objective weights solely to avoid uncertainty with subjective weighting [79,89,105]. Eleven articles (26.8%) did not use any type of weighting method (Table S3).…”

Section: Weighting Methodsmentioning

confidence: 99%

Development of a Generic Decision Tree for the Integration of Multi-Criteria Decision-Making (MCDM) and Multi-Objective Optimization (MOO) Methods under Uncertainty to Facilitate Sustainability Assessment: A Methodical Review

Ferdous,

Bensebaa,

Milani

et al. 2024

Sustainability

View full text Add to dashboard Cite

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“…Like GAs, the relative simplicity of PSO makes it ideal for use in multi-objective optimization. As a result, it has been used widely in both reservoir operation and design applications [32][33][34]. In a comparative analysis between GAs and PSO at a single dam, PSO outperformed the GAs in terms of solution accuracy, convergence rate, and run time to reach global optima [34].…”

Section: Introductionmentioning

confidence: 99%

On the Optimized Management of Activated Distributed Storage Systems: A Novel Approach to Flood Mitigation

Post,

Quintero,

Krajewski

2024

Water

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New flood records are being set across the world as precipitation patterns change due to a warming climate. Despite the presence of longstanding water management infrastructure like levees and reservoirs, this rise in flooding has been met with property damage, loss of life, and hundreds of billions in economic impact, suggesting the need for new solutions. In this work, the authors suggest the active management of distributed networks of ponds, wetlands and retention basins that already exist across watersheds for the mitigation of flood damages. As an example of this approach, we investigate optimal control of the gated outlets of 130 such locations within a small watershed using linear programming, genetic algorithms, and particle swarm optimization, with the objective of reducing downstream flow and maximizing basin storage. When compared with passive operation (i.e., no gated outlets) and a uniformly applied active management scheme designed to store water during heavy rainfall, the optimal control techniques (1) reduce the magnitudes of peak flow events by up to 10%, (2) reduce the duration of flood crests for up to several days, and (3) preserve additional storage across the watershed for future rainfall events when compared with active management. Combined, these findings provide both a better understanding of dynamically controlled distributed storage as a flood fighting technique and a springboard for future work aimed at its use for reducing flood impacts.

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“…Several types of multicriteria analysis have been studied to control risks in water management (Nematollahi et al 2022). The management of water resources is an important decision-making factor that signi cantly in uences the planning of these resources (Imteaz and Hossain, 2023).…”

Section: Introductionmentioning

confidence: 99%

Water quality parameters in source water: multivariate analysis of surface water and groundwater supply on data from 4 supply systems in Brazil

Dallmann,

Beltrame,

Valentini

et al. 2023

Preprint

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In this research, multivariate statistical analysis was performed to assess the water quality of 4 important drinking water sources in the state of Rio Grande do Sul (RS), Brazil. For this, nineteen water quality parameters (WQP) were applied twice a year, for the period 2013-2018, to assess water quality from different sources. The evaluation was conducted on tree water surface (SWS) and one groundwater source (GWS), separately. Analysis of outliers, Shapiro-Wilk normality test, non-parametric Kruskal-Wallis test, Spearman correlation analysis, hierarchical cluster analysis and the Ward method were carried out to identify the quality of water from different sources. There were higher coefficients of variation for metals, color, turbidity, and total phosphorus. The multivariate analysis pointed out that variables with the highest correlation and grouping in the springs indicate the movement of soil particles into water bodies and their degradation, due to the lack of protection in the areas of these relevant sources of supply.

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A Multi-criteria Decision-making Optimization Model for Flood Management in Reservoirs

Cited by 14 publications

References 32 publications

Development of a Generic Decision Tree for the Integration of Multi-Criteria Decision-Making (MCDM) and Multi-Objective Optimization (MOO) Methods under Uncertainty to Facilitate Sustainability Assessment: A Methodical Review

Development of a Generic Decision Tree for the Integration of Multi-Criteria Decision-Making (MCDM) and Multi-Objective Optimization (MOO) Methods under Uncertainty to Facilitate Sustainability Assessment: A Methodical Review

On the Optimized Management of Activated Distributed Storage Systems: A Novel Approach to Flood Mitigation

Water quality parameters in source water: multivariate analysis of surface water and groundwater supply on data from 4 supply systems in Brazil

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