Evidence map›Paper›PMID 35250256›Full record

ReviewArchives of computational methods in engineering : state of the art reviews2022

A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms.

Vivien Lai, Yuk Feng Huang, Chai Hoon Koo, Ali Najah Ahmed, Ahmed El-Shafie

Abstract readReview
In one paragraph

Review in Archives of computational methods in engineering : state of the art reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Vivien LaiDepartment of Civil Engineering, Universiti Tunku Abdul Rahman, Selangor, Malaysia.
Yuk Feng HuangDepartment of Civil Engineering, Universiti Tunku Abdul Rahman, Selangor, Malaysia.
Chai Hoon KooDepartment of Civil Engineering, Universiti Tunku Abdul Rahman, Selangor, Malaysia.
Ali Najah AhmedInstitute of Engineering Infrastructures (IEI), Universiti Tenaga Nasional (UNITEN), 43000 Selangor, Malaysia.
Ahmed El-ShafieDepartment of Civil Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reservoir operation optimisation secures benefits, such as optimising energy production while minimising the possibility of flooding, operating costs, and water scarcity, at the lowest possible cost. This paper carries reviews of research on reservoir optimisation models and the consequential challenges of optimally operating reservoir operations. An introductory section is given to the background of reservoir operations and the current concerns on the optimal reservoir operations, for the decision-makers and stakeholders. Next, the review covered the recent ten years (between 2011 and 2021), on the recent research developments in innovation and techniques of reservoir operation optimisation. Further reviews on the conventional techniques that are the traditional methods, linear programming, nonlinear programming, and dynamic programming are discussed. Enhancements to the techniques in improving the drawbacks of the traditional techniques in optimisation of reservoir policies are next explained and evaluated. Recent advances in applying metaheuristics optimisation algorithms beneficial to the reservoir operations are explained, including the advantages and hinderances. A comprehensive tabulated and categorised review according to the classification of reservoir models, evaluation methods, and reservoir systems is given.

Identifiers

PMID35250256
PMCPMC8877748

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.