Application of Artificial Bee Colony and Gravitational Search Algorithm in Reservoir Optimization

This paper presented the application of Artificial Bee Colony (ABC) and Gravitational Search Algorithm (GSA) in reservoir optimization. ABC is an algorithm based on the foraging behaviour of bee while GSA imitates the gravitational processes. These algorithms were used to minimize the irrigation rel...

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Bibliographic Details
Published inWater resources management Vol. 30; no. 7; pp. 2497 - 2516
Main Authors Ahmad, Asmadi, Razali, Siti Fatin Mohd, Mohamed, Zawawi Samba, El-shafie, Ahmed
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.05.2016
Springer Nature B.V
Subjects
Algorithms
Apoidea
Atmospheric Sciences
Civil Engineering
Convergence
Dynamic programming
Earth and Environmental Science
Earth Sciences
Engineering
Environment
foraging
Foraging behavior
Fuzzy logic
Genetic algorithms
Geotechnical Engineering & Applied Earth Sciences
Gravitation
Hydrogeology
Hydrology
Hydrology/Water Resources
Irrigation
Linear programming
Malaysia
Optimization
Optimization algorithms
Optimization techniques
Performance evaluation
Reservoirs
Route optimization
Search algorithms
Studies
Swarm intelligence
system optimization
Water resources
Water resources management
Water supply
Malaysia
ISEW, Malaysia
Gravitational search algorithm
Reservoir performance measure
Artificial bee colony
Reservoir optimization
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ISSN0920-4741
1573-1650
DOI10.1007/s11269-016-1304-z

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Summary:This paper presented the application of Artificial Bee Colony (ABC) and Gravitational Search Algorithm (GSA) in reservoir optimization. ABC is an algorithm based on the foraging behaviour of bee while GSA imitates the gravitational processes. These algorithms were used to minimize the irrigation release deficit for Timah Tasoh Dam located at the Northern part of Peninsular Malaysia. Results proved the superiority of the ABC compared to GSA with regards to faster convergence rate, stability, higher reliability and lower vulnerability indexes, while GSA is better in the resiliency indicator measure. Finally, both algorithms can be used to solve reservoir optimization problem with their own unique capability and to improve the performance of the reservoir compared to the existing reservoir standard operation procedure.
Bibliography:http://dx.doi.org/10.1007/s11269-016-1304-z
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-016-1304-z