IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v202y2010i1p60-72.html
   My bibliography  Save this article

A multiobjective immune algorithm based on a multiple-affinity model

Author

Listed:
  • Hu, Zhi-Hua

Abstract

This paper presents a new multiobjective immune algorithm based on a multiple-affinity model inspired by immune system (MAM-MOIA). The multiple-affinity model builds the relationship model among main entities and concepts in multiobjective problems (MOPs) and multiobjective evolutionary algorithms (MOEAs), including feasible solution, variable space, objective space, Pareto-optimal set, ranking and crowding distance. In the model, immune operators including clonal proliferation, hypermutation and immune suppression are designed to proliferate superior antibodies and suppress the inferiors. MAM-MOIA is compared with NSGA-II, SPEA2 and NNIA in solving the ZDT and DTLZ standard test problems. The experimental study based on three performance metrics including coverage of two sets, convergence and spacing proves that MAM-MOIA is effective for solving MOPs.

Suggested Citation

  • Hu, Zhi-Hua, 2010. "A multiobjective immune algorithm based on a multiple-affinity model," European Journal of Operational Research, Elsevier, vol. 202(1), pages 60-72, April.
    • Handle: RePEc:eee:ejores:v:202:y:2010:i:1:p:60-72
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00346-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Tan, K.C. & Goh, C.K. & Mamun, A.A. & Ei, E.Z., 2008. "An evolutionary artificial immune system for multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 187(2), pages 371-392, June.
    2. Elaoud, Semya & Loukil, Taicir & Teghem, Jacques, 2007. "The Pareto fitness genetic algorithm: Test function study," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1703-1719, 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. Lei, Yu & Gong, Maoguo & Zhang, Jun & Li, Wei & Jiao, Licheng, 2014. "Resource allocation model and double-sphere crowding distance for evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 234(1), pages 197-208.

    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. Chen, Jianyong & Lin, Qiuzhen & Ji, Zhen, 2010. "A hybrid immune multiobjective optimization algorithm," European Journal of Operational Research, Elsevier, vol. 204(2), pages 294-302, July.
    2. Dengsheng Wu & Xiaoqian Zhu & Jie Wan & Chunbing Bao & Jianping Li, 2019. "A Multiobjective Optimization Approach for Selecting Risk Response Strategies of Software Project: From the Perspective of Risk Correlations," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 339-364, January.
    3. Gong, Wenyin & Cai, Zhihua, 2009. "An improved multiobjective differential evolution based on Pareto-adaptive [epsilon]-dominance and orthogonal design," European Journal of Operational Research, Elsevier, vol. 198(2), pages 576-601, October.
    4. Singh, Bindeshwar & Mukherjee, V. & Tiwari, Prabhakar, 2015. "A survey on impact assessment of DG and FACTS controllers in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 846-882.
    5. Gabriel H Greve & Kenneth M Hopkinson & Gary B Lamont, 2018. "Evolutionary sensor allocation for the Space Surveillance Network," The Journal of Defense Modeling and Simulation, , vol. 15(3), pages 303-322, July.
    6. Xiaoya Ma & Xiang Zhao, 2015. "Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China," Sustainability, MDPI, vol. 7(11), pages 1-20, November.
    7. Lei, Yu & Gong, Maoguo & Zhang, Jun & Li, Wei & Jiao, Licheng, 2014. "Resource allocation model and double-sphere crowding distance for evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 234(1), pages 197-208.
    8. Goh, C.K. & Tan, K.C. & Liu, D.S. & Chiam, S.C., 2010. "A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design," European Journal of Operational Research, Elsevier, vol. 202(1), pages 42-54, April.
    9. Chen, Min-Rong & Lu, Yong-Zai, 2008. "A novel elitist multiobjective optimization algorithm: Multiobjective extremal optimization," European Journal of Operational Research, Elsevier, vol. 188(3), pages 637-651, August.
    10. Soroudi, Alireza & Ehsan, Mehdi & Zareipour, Hamidreza, 2011. "A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources," Renewable Energy, Elsevier, vol. 36(1), pages 179-188.
    11. Lin, Shih-Wei & Ying, Kuo-Ching, 2013. "Minimizing makespan in a blocking flowshop using a revised artificial immune system algorithm," Omega, Elsevier, vol. 41(2), pages 383-389.
    12. Lochtefeld, Darrell F. & Ciarallo, Frank W., 2015. "Multi-objectivization Via Decomposition: An analysis of helper-objectives and complete decomposition," European Journal of Operational Research, Elsevier, vol. 243(2), pages 395-404.
    13. Chan, C.W. & Siqueiros, E. & Ling-Chin, J. & Royapoor, M. & Roskilly, A.P., 2015. "Heat utilisation technologies: A critical review of heat pipes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 615-627.

    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:202:y:2010:i:1:p:60-72. 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.