IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v217y2012i2p404-416.html
   My bibliography  Save this article

An efficient Differential Evolution based algorithm for solving multi-objective optimization problems

Author

Listed:
  • Ali, Musrrat.
  • Siarry, Patrick
  • Pant, Millie.

Abstract

In the present study, a modified variant of Differential Evolution (DE) algorithm for solving multi-objective optimization problems is presented. The proposed algorithm, named Multi-Objective Differential Evolution Algorithm (MODEA) utilizes the advantages of Opposition-Based Learning for generating an initial population of potential candidates and the concept of random localization in mutation step. Finally, it introduces a new selection mechanism for generating a well distributed Pareto optimal front. The performance of proposed algorithm is investigated on a set of nine bi-objective and five tri-objective benchmark test functions and the results are compared with some recently modified versions of DE for MOPs and some other Multi Objective Evolutionary Algorithms (MOEAs). The empirical analysis of the numerical results shows the efficiency of the proposed algorithm.

Suggested Citation

  • Ali, Musrrat. & Siarry, Patrick & Pant, Millie., 2012. "An efficient Differential Evolution based algorithm for solving multi-objective optimization problems," European Journal of Operational Research, Elsevier, vol. 217(2), pages 404-416.
    • Handle: RePEc:eee:ejores:v:217:y:2012:i:2:p:404-416
    DOI: 10.1016/j.ejor.2011.09.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711008538
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2011.09.025?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. Deb, Kalyanmoy & Tiwari, Santosh, 2008. "Omni-optimizer: A generic evolutionary algorithm for single and multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1062-1087, March.
    2. Kaelo, P. & Ali, M.M., 2006. "A numerical study of some modified differential evolution algorithms," European Journal of Operational Research, Elsevier, vol. 169(3), pages 1176-1184, March.
    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. Liu, Ruochen & Li, Jianxia & fan, Jing & Mu, Caihong & Jiao, Licheng, 2017. "A coevolutionary technique based on multi-swarm particle swarm optimization for dynamic multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1028-1051.
    2. Lunardi, Willian T. & Birgin, Ernesto G. & Ronconi, Débora P. & Voos, Holger, 2021. "Metaheuristics for the online printing shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 293(2), pages 419-441.
    3. Mahalec, Vladimir & Chen, Yingwu & Liu, Xiaolu & He, Renjie & Sun, Kai, 2015. "Reconfiguration of satellite orbit for cooperative observation using variable-size multi-objective differential evolutionAuthor-Name: Chen, Yingguo," European Journal of Operational Research, Elsevier, vol. 242(1), pages 10-20.
    4. Fan, Qinqin & Yan, Xuefeng & Zhang, Yilian, 2018. "Auto-selection mechanism of differential evolution algorithm variants and its application," European Journal of Operational Research, Elsevier, vol. 270(2), pages 636-653.
    5. Muhsen, Dhiaa Halboot & Ghazali, Abu Bakar & Khatib, Tamer & Abed, Issa Ahmed & Natsheh, Emad M., 2016. "Sizing of a standalone photovoltaic water pumping system using a multi-objective evolutionary algorithm," Energy, Elsevier, vol. 109(C), pages 961-973.
    6. Om Prakash Verma & Toufiq Haji Mohammed & Shubham Mangal & Gaurav Manik, 2018. "Optimization of steam economy and consumption of heptad’s effect evaporator system in Kraft recovery process," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 111-130, February.
    7. Zhalechian, M. & Torabi, S. Ali & Mohammadi, M., 2018. "Hub-and-spoke network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 20-43.
    8. Qinqin Fan & Xuefeng Yan, 2018. "Multi-objective modified differential evolution algorithm with archive-base mutation for solving multi-objective $$p$$ p -xylene oxidation process," Journal of Intelligent Manufacturing, Springer, vol. 29(1), pages 35-49, January.
    9. Wang, Dujuan & Yin, Yunqiang & Cheng, T.C.E., 2018. "Parallel-machine rescheduling with job unavailability and rejection," Omega, Elsevier, vol. 81(C), pages 246-260.
    10. Yu, Yang & Tang, Jiafu & Gong, Jun & Yin, Yong & Kaku, Ikou, 2014. "Mathematical analysis and solutions for multi-objective line-cell conversion problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 774-786.
    11. Ma, Xuemin & Yang, Jingming & Sun, Hao & Hu, Ziyu & Wei, Lixin, 2021. "Feature information prediction algorithm for dynamic multi-objective optimization problems," European Journal of Operational Research, Elsevier, vol. 295(3), pages 965-981.
    12. Wei Wang & Jingjie Chen & Qi Liu & Zhaoxia Guo, 2018. "Green Project Planning with Realistic Multi-Objective Consideration in Developing Sustainable Port," Sustainability, MDPI, vol. 10(7), pages 1-15, July.

    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. Vahid Baradaran & Amir Hossein Hosseinian, 2020. "A bi-objective model for redundancy allocation problem in designing server farms: mathematical formulation and solution approaches," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(5), pages 935-952, October.
    2. Liagkouras, Konstantinos & Metaxiotis, Konstantinos, 2021. "Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1019-1036.
    3. M. Ali & W. Zhu, 2013. "A penalty function-based differential evolution algorithm for constrained global optimization," Computational Optimization and Applications, Springer, vol. 54(3), pages 707-739, April.
    4. K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    5. Dan Yan & Saskia E. Werners & He Qing Huang & Fulco Ludwig, 2016. "Identifying and Assessing Robust Water Allocation Plans for Deltas Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5421-5435, November.
    6. Andreas C. Nearchou & Sotiris L. Omirou, 2024. "Self-Adaptive Biased Differential Evolution for Scheduling Against Common Due Dates," SN Operations Research Forum, Springer, vol. 5(2), pages 1-29, June.
    7. Maysam Safe & Seyed Khazraee & Payam Setoodeh & Abdolhosein Jahanmiri, 2013. "Model reduction and optimization of a reactive dividing wall batch distillation column inspired by response surface methodology and differential evolution," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 19(1), pages 29-50.
    8. Mohsen Davoodi & Hamed Jafari Kaleybar & Morris Brenna & Dario Zaninelli, 2023. "Energy Management Systems for Smart Electric Railway Networks: A Methodological Review," Sustainability, MDPI, vol. 15(16), pages 1-35, August.
    9. Wang, Long & Wu, Jianghai & Wang, Tongguang & Han, Ran, 2020. "An optimization method based on random fork tree coding for the electrical networks of offshore wind farms," Renewable Energy, Elsevier, vol. 147(P1), pages 1340-1351.
    10. Ziqian Wang & Xin Huang & Yan Zhang & Danju Lv & Wei Li & Zhicheng Zhu & Jian’e Dong, 2024. "Modeling and Solving the Knapsack Problem with a Multi-Objective Equilibrium Optimizer Algorithm Based on Weighted Congestion Distance," Mathematics, MDPI, vol. 12(22), pages 1-19, November.
    11. Zio, E. & Viadana, G., 2011. "Optimization of the inspection intervals of a safety system in a nuclear power plant by Multi-Objective Differential Evolution (MODE)," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1552-1563.
    12. Piotrowski, Adam P. & Napiorkowski, Jaroslaw J. & Kiczko, Adam, 2012. "Differential Evolution algorithm with Separated Groups for multi-dimensional optimization problems," European Journal of Operational Research, Elsevier, vol. 216(1), pages 33-46.
    13. Wang, Long & Wang, Tongguang & Wu, Jianghai & Chen, Guoping, 2017. "Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design," Energy, Elsevier, vol. 120(C), pages 346-361.
    14. du Plessis, Mathys C. & Engelbrecht, Andries P., 2012. "Using Competitive Population Evaluation in a differential evolution algorithm for dynamic environments," European Journal of Operational Research, Elsevier, vol. 218(1), pages 7-20.
    15. Biswas (Raha), Syamasree & Mandal, Kamal Krishna & Chakraborty, Niladri, 2016. "Pareto-efficient double auction power transactions for economic reactive power dispatch," Applied Energy, Elsevier, vol. 168(C), pages 610-627.
    16. K. Liagkouras & K. Metaxiotis & G. Tsihrintzis, 2022. "Incorporating environmental and social considerations into the portfolio optimization process," Annals of Operations Research, Springer, vol. 316(2), pages 1493-1518, September.
    17. Kaelo, P. & Ali, M.M., 2007. "Integrated crossover rules in real coded genetic algorithms," European Journal of Operational Research, Elsevier, vol. 176(1), pages 60-76, January.
    18. Rashida Adeeb Khanum & Muhammad Asif Jan & Nasser Mansoor Tairan & Wali Khan Mashwani, 2016. "Hybridization of Adaptive Differential Evolution with an Expensive Local Search Method," Journal of Optimization, Hindawi, vol. 2016, pages 1-14, July.
    19. Long Wang & Jianghai Wu & Zeling Tang & Tongguang Wang, 2019. "An Integration Optimization Method for Power Collection Systems of Offshore Wind Farms," Energies, MDPI, vol. 12(20), pages 1-16, October.
    20. K. Liagkouras & K. Metaxiotis, 2018. "A new efficiently encoded multiobjective algorithm for the solution of the cardinality constrained portfolio optimization problem," Annals of Operations Research, Springer, vol. 267(1), pages 281-319, August.

    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:eee:ejores:v:217:y:2012:i:2:p:404-416. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.