Skip to main content
SpringerLink
Log in

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

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Ahmad A, El-Shafie A, Razali SFM, Mohamad ZS (2014) Reservoir optimization in water resources: a review. Water Resour Manag 28(11):3391–3405

    Article  Google Scholar 

  • Baltar AM, Fontane DG (2008) Use of multiobjective particle swarm optimization in water resources management. J Water Resour Plann Manage 134(3):257–265

    Article  Google Scholar 

  • Barros MT, Tsai FT, Yang S-l, Lopes JE, Yeh WW (2003) Optimization of large-scale hydropower system operations. J Water Resour Plann Manage 129(3):178–188

  • Braga BP Jr, Yen WW-G, Becker L, Barros MT (1991) Stochastic optimization of multiple-reservoir-system operation. J Water Resour Plan Manag 117(4):471–481

    Article  Google Scholar 

  • Chang L-C, Chang F-J (2001) Intelligent control for modelling of real-time reservoir operation. Hydrol Process 15(9):1621–1634

  • Chang F-J, Chen L (1998) Real-coded genetic algorithm for rule-based flood control reservoir management. Water Resour Manage 12(3):185–198

  • Chatterjee A, Mahanti GK, Pathak NN (2010) Comparative performance of gravitational search algorithm and modified particle swarm optimization algorithm for synthesis of thinned scanned concentric ring array antenna. Progr Electromagn Res B 25:331–348

    Article  Google Scholar 

  • Chen L, McPhee J, Yeh WWG (2007) A diversified multiobjective GA for optimizing reservoir rule curves. Adv Water Resour 30(5):1082–1093

    Article  Google Scholar 

  • Crawley PD, Dandy GC (1993) Optimal operation of multiple-reservoir system. J Water Resour Plan Manag 119(1):1–17

    Article  Google Scholar 

  • Dariane AB, Sarani S (2013) Application of intelligent water drops algorithm in reservoir operation. Water Resour Manag 27(14):4827–4843

    Article  Google Scholar 

  • de Castro LN, & Timmis J (2002) An artificial immune network for multimodal function optimization. Evolutionary Computation, 2002. CEC’02. Proceedings of the 2002 Congress on, IEEE

  • De Meyer K, Bishop J, Nasuto S (2003) Stochastic diffusion: using recruitment for search. Evolvability and interaction: evolutionary substrates of communication, signalling, and perception in the dynamics of social complexity. In: McOwan P, Dautenhahn K, Nehaniv CL (Ed.). Technical Report 393: 60–65X

  • Duman S, Güvenç U, Sönmez Y, Yörükeren N (2012) Optimal power flow using gravitational search algorithm. Energy Convers Manag 59:86–95

  • Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. Micro Machine and Human Science, 1995. MHS’95. Proceedings of the Sixth International Symposium on, IEEE

  • Fayaed S, El-Shafie A, Jaafar O (2013) Integrated Artificial Neural Network (ANN) and Stochastic Dynamic Programming (SDP) model for optimal release policy. Water Resour Manag 27(10):3679–3696

    Article  Google Scholar 

  • Gomez A, Salhi S (2014) Solving capacitated vehicle routing problem by artificial bee colony algorithm. Computational Intelligence in Production and Logistics Systems (CIPLS), 2014 I.E. Symposium on, IEEE

  • Guo Z (2012) A hybrid optimization algorithm based on artificial bee colony and gravitational search algorithm. Int J Digital Content Technol Appl 6(17)

  • Hashimoto T, Stedinger JR, Loucks DP (1982) Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water Resour Res 18(1):14–20

    Article  Google Scholar 

  • Hossain MS, El-shafie A (2013) Intelligent systems in optimizing reservoir operation policy: a review. Water Resour Manag 27(9):3387–3407

    Article  Google Scholar 

  • Karaboga N (2009) A new design method based on artificial bee colony algorithm for digital IIR filters. J Franklin Inst 346(4):328–348

    Article  Google Scholar 

  • Karaboga D, Akay B (2009) A comparative study of Artificial Bee Colony algorithm. Appl Math Comput 214(1):108–132

    Article  Google Scholar 

  • Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Glob Optim 39(3):459–471

    Article  Google Scholar 

  • Karaboga D, Basturk B (2008) On the performance of artificial bee colony (ABC) algorithm. Appl Soft Comput 8(1):687–697

    Article  Google Scholar 

  • Kumar ARS, Goyal M, Ojha CSP, Singh RD, Swamee PK, Nema RK (2013) Application of ANN, fuzzy logic and decision tree algorithms for the development of reservoir operating rules. Water Resour Manag 27(3):911–925

    Article  Google Scholar 

  • Li X-G, Wei X (2007) An improved genetic algorithm-simulated annealing hybrid algorithm for the optimization of multiple reservoirs. Water Resour Manag 22(8):1031–1049

    Article  Google Scholar 

  • Loucks DP, Van Beek E, Stedinger JR, Dijkman JP, Villars MT (2005) Water resources systems planning and management: an introduction to methods, models and applications. UNESCO, Paris

    Google Scholar 

  • Mandal SK, Chan FT, Tiwari M (2012) Leak detection of pipeline: an integrated approach of rough set theory and artificial bee colony trained SVM. Expert Syst Appl 39(3):3071–3080

    Article  Google Scholar 

  • Mays LW, Tung Y-K (1992). Hydrosystems engineering & management. McGraw Hill

  • Meraji SH, Afshar M, Afshar A (2005) Reservoir operation by particle swarm optimization algorithm. Proceedings of the 7th International Conference of Civil Engineering (Icce7th), Tehran, Iran

  • Molga M, Smutnicki C (2005) Test functions for optimization needs. North-Eastern Hill University, Shillong

    Google Scholar 

  • Omar N, Eng Chieh O, Adam A, Hasim SH, Zainal Abidin AF, Jaafar HI, Zakaria H, Jefery H, Nordin NA, Khairuddin O (2014) An experimental study of the application of gravitational search algorithm in solving route optimization problem for holes drilling process. International Conference Recent Treads in Engineering & Technology, Batam, 7–10

  • Ozturk A, Cobanli S, Erdogmus P, Tosun S (2010) Reactive power optimization with artificial bee colony algorithm. Sci Res Essays 5(19):2848–2857

    Google Scholar 

  • Pasha MFK, Yeasmin D, Rentch JW (2015) Dam-lake operation to optimize fish habitat. Environ Process 2(4):631–645

    Article  Google Scholar 

  • Rao RS, Narasimham SVL, Ramalinga Raju M, Srinivasa Rao A (2011) Optimal network reconfiguration of large-scale distribution system using harmony search algorithm. IEEE Trans Power Syst 26(3):1080–1088

    Article  Google Scholar 

  • Rashedi E, Nezamabadi-Pour H, Saryazdi S, Farsangi MM (2007) Allocation of static var compensator using gravitational search algorithm. First Joint Congress on Fuzzy and Intelligent Systems, Iran

  • Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) GSA: a gravitational search algorithm. Inf Sci 179(13):2232–2248

    Article  Google Scholar 

  • Rashedi E, Nezamabadi-pour H, Saryazdi S (2011) Filter modeling using gravitational search algorithm. Eng Appl Artif Intell 24(1):117–122

  • Reddy MJ, Nagesh Kumar D (2007) Multi-objective particle swarm optimization for generating optimal trade-offs in reservoir operation. Hydrol Process 21(21):2897–2909

    Article  Google Scholar 

  • Sabat SL, Udgata SK, Abraham A (2010) Artificial bee colony algorithm for small signal model parameter extraction of MESFET. Eng Appl Artif Intell 23(5):689–694

    Article  Google Scholar 

  • Shah Hosseini H (2007) Problem solving by intelligent water drops. Evolutionary Computation, 2007. CEC 2007. IEEE Congress on, IEEE

  • Van Loon A, Van Lanen H (2015) Testing the observation-modelling framework to distinguish between hydrological drought and water scarcity in case studies around Europe

  • Walker WE, Loucks DP, Carr G (2015) Social responses to water management decisions. Environ Process 2(3):485–509

    Article  Google Scholar 

  • Wardlaw R, Sharif M (1999) Evaluation of genetic algorithms for optimal reservoir system operation. J Water Resour Plan Manag 125(1):25–33

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National University of Malaysia, Bangi, Malaysia

    Asmadi Ahmad, Siti Fatin Mohd Razali & Zawawi Samba Mohamed

  2. University of Malaya, Kuala Lumpur, Malaysia

    Ahmed El-shafie

Authors
  1. Asmadi Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Siti Fatin Mohd Razali
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zawawi Samba Mohamed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmed El-shafie
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Asmadi Ahmad.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ahmad, A., Razali, S.F.M., Mohamed, Z.S. et al. The Application of Artificial Bee Colony and Gravitational Search Algorithm in Reservoir Optimization. Water Resour Manage 30, 2497–2516 (2016). https://doi.org/10.1007/s11269-016-1304-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-016-1304-z

Keywords

Search

Navigation