IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v32y2018i12d10.1007_s11269-018-2034-1.html
   My bibliography  Save this article

Multi Objective Optimization with a New Evolutionary Algorithm

Author

Listed:
  • Samaneh Seifollahi-Aghmiuni

    (Stockholm University)

  • Omid Bozorg Haddad

    (University of Tehran)

Abstract

Various objectives are mainly met through decision making in real world. Achieving desirable condition for all objectives simultaneously is a necessity for conflicting objectives. This concept is called multi objective optimization widely used nowadays. In this study, a new algorithm, comprehensive evolutionary algorithm (CEA), is developed based on general concepts of evolutionary algorithms that can be applied for single or multi objective problems with a fixed structure. CEA is validated through solving several mathematical multi objective problems and the obtained results are compared with the results of the non-dominated sorting genetic algorithm II (NSGA-II). Also, CEA is applied for solving a reservoir operation management problem. Comparisons show that CEA has a desirable performance in multi objective problems. The decision space is accurately assessed by CEA in considered problems and the obtained solutions’ set has a great extent in the objective space of each problem. Also, CEA obtains more number of solutions on the Pareto than NSGA-II for each considered problem. Although the total run time of CEA is longer than NSGA-II, solution set obtained by CEA is about 32, 4.4 and 1.6% closer to the optimum results in comparison with NSGA-II in the first, second and third mathematical problem, respectively. It shows the high reliability of CEA’s results in solving multi objective problems.

Suggested Citation

  • Samaneh Seifollahi-Aghmiuni & Omid Bozorg Haddad, 2018. "Multi Objective Optimization with a New Evolutionary Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(12), pages 4013-4030, September.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:12:d:10.1007_s11269-018-2034-1
    DOI: 10.1007/s11269-018-2034-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-018-2034-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-018-2034-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Niknam, Taher & Meymand, Hamed Zeinoddini & Mojarrad, Hasan Doagou, 2011. "An efficient algorithm for multi-objective optimal operation management of distribution network considering fuel cell power plants," Energy, Elsevier, vol. 36(1), pages 119-132.
    2. Lipowski, Adam & Lipowska, Dorota, 2012. "Roulette-wheel selection via stochastic acceptance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2193-2196.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dong Liu & Tao Bai & Mingjiang Deng & Jia Xu & Xiaoting Wei, 2024. "Multi-Objective Ecological Operation of Large-Scale Reservoir-Gate System Coupled with Vegetation Priority Irrigation in Arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(13), pages 5097-5122, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haddadian, Hossein & Noroozian, Reza, 2017. "Optimal operation of active distribution systems based on microgrid structure," Renewable Energy, Elsevier, vol. 104(C), pages 197-210.
    2. Chen, Enming & Zhou, Zhongbao & Li, Ruiyang & Chang, Zhongxiang & Shi, Jianmai, 2024. "The multi-fleet delivery problem combined with trucks, tricycles, and drones for last-mile logistics efficiency requirements under multiple budget constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    3. Andrés Alfonso Rosales-Muñoz & Luis Fernando Grisales-Noreña & Jhon Montano & Oscar Danilo Montoya & Alberto-Jesus Perea-Moreno, 2021. "Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    4. Finke, Jonas & Bertsch, Valentin, 2022. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," MPRA Paper 115504, University Library of Munich, Germany.
    5. Hu, Yusha & Li, Jigeng & Hong, Mengna & Ren, Jingzheng & Lin, Ruojue & Liu, Yue & Liu, Mengru & Man, Yi, 2019. "Short term electric load forecasting model and its verification for process industrial enterprises based on hybrid GA-PSO-BPNN algorithm—A case study of papermaking process," Energy, Elsevier, vol. 170(C), pages 1215-1227.
    6. Mehmet Burak Şenol & Ekrem Alper Murat, 2023. "A sequential solution heuristic for continuous facility layout problems," Annals of Operations Research, Springer, vol. 320(1), pages 355-377, January.
    7. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
    8. Niknam, Taher & Kavousi Fard, Abdollah & Baziar, Aliasghar, 2012. "Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants," Energy, Elsevier, vol. 42(1), pages 563-573.
    9. Baowei Wang & Peng Zhao, 2020. "An Adaptive Image Watermarking Method Combining SVD and Wang-Landau Sampling in DWT Domain," Mathematics, MDPI, vol. 8(5), pages 1-20, May.
    10. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).
    11. Zhang, Houcheng & Chen, Liwei & Zhang, Jinjie & Chen, Jincan, 2014. "Performance analysis of a direct carbon fuel cell with molten carbonate electrolyte," Energy, Elsevier, vol. 68(C), pages 292-300.
    12. Sanseverino, Eleonora Riva & Di Silvestre, Maria Luisa & Ippolito, Mariano Giuseppe & De Paola, Alessandra & Lo Re, Giuseppe, 2011. "An execution, monitoring and replanning approach for optimal energy management in microgrids," Energy, Elsevier, vol. 36(5), pages 3429-3436.
    13. Fathy, Ahmed, 2022. "A novel artificial hummingbird algorithm for integrating renewable based biomass distributed generators in radial distribution systems," Applied Energy, Elsevier, vol. 323(C).
    14. Pascal P Klamser & Pawel Romanczuk, 2021. "Collective predator evasion: Putting the criticality hypothesis to the test," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-21, March.
    15. Abbasi, Ali Reza & Seifi, Ali Reza, 2015. "Considering cost and reliability in electrical and thermal distribution networks reinforcement planning," Energy, Elsevier, vol. 84(C), pages 25-35.
    16. Doagou-Mojarrad, Hasan & Gharehpetian, G.B. & Rastegar, H. & Olamaei, Javad, 2013. "Optimal placement and sizing of DG (distributed generation) units in distribution networks by novel hybrid evolutionary algorithm," Energy, Elsevier, vol. 54(C), pages 129-138.
    17. Shuya Zhong & Yizeng Chen & Jian Zhou & Yuanyuan Liu, 2017. "An interactive satisficing approach for multi-objective optimization with uncertain parameters," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 535-547, March.
    18. Maryam Dehghan Chenary & Arman Ferdowsi & Richard F. Hartl, 2024. "A Pareto-Based Clustering Approach for Solving a Bi-Objective Mobile Hub Location Problem with Congestion," Logistics, MDPI, vol. 8(4), pages 1-30, December.
    19. Ojer, Jaume & López, Álvaro G. & Used, Javier & Sanjuán, Miguel A.F., 2022. "A stochastic hybrid model with a fast concentration bias for chemotactic cellular attraction," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    20. Arandian, B. & Ardehali, M.M., 2017. "Effects of environmental emissions on optimal combination and allocation of renewable and non-renewable CHP technologies in heat and electricity distribution networks based on improved particle swarm ," Energy, Elsevier, vol. 140(P1), pages 466-480.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:32:y:2018:i:12:d:10.1007_s11269-018-2034-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.