Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies

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  • Additional Information
    • Publication Information:
      Hindawi Limited, 2019.
    • Publication Date:
      2019
    • Collection:
      LCC:Engineering (General). Civil engineering (General)
      LCC:Mathematics
    • Abstract:
      In order to solve the multiobjective optimization problems efficiently, this paper presents a hybrid multiobjective optimization algorithm which originates from invasive weed optimization (IWO) and multiobjective evolutionary algorithm based on decomposition (MOEA/D), a popular framework for multiobjective optimization. IWO is a simple but powerful numerical stochastic optimization method inspired from colonizing weeds; it is very robust and well adapted to changes in the environment. Based on the smart and distinct features of IWO and MOEA/D, we introduce multiobjective invasive weed optimization algorithm based on decomposition, abbreviated as MOEA/D-IWO, and try to combine their excellent features in this hybrid algorithm. The efficiency of the algorithm both in convergence speed and optimality of results are compared with MOEA/D and some other popular multiobjective optimization algorithms through a big set of experiments on benchmark functions. Experimental results show the competitive performance of MOEA/D-IWO in solving these complicated multiobjective optimization problems.
    • File Description:
      electronic resource
    • ISSN:
      1024-123X
      1563-5147
    • Relation:
      https://doaj.org/toc/1024-123X; https://doaj.org/toc/1563-5147
    • Accession Number:
      10.1155/2019/6943921
    • Rights:
      Journal Licence: CC BY
    • Accession Number:
      edsdoj.2d67917e69c6411c9dcfa46fc36342a9
  • Citations
    • ABNT:
      YANYAN TAN et al. Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies. Mathematical Problems in Engineering, [s. l.], 2019. Disponível em: . Acesso em: 18 set. 2019.
    • AMA:
      Yanyan Tan, Xue Lu, Yan Liu, Qiang Wang, Huaxiang Zhang. Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies. Mathematical Problems in Engineering. 2019. doi:10.1155/2019/6943921.
    • APA:
      Yanyan Tan, Xue Lu, Yan Liu, Qiang Wang, & Huaxiang Zhang. (2019). Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies. Mathematical Problems in Engineering. https://doi.org/10.1155/2019/6943921
    • Chicago/Turabian: Author-Date:
      Yanyan Tan, Xue Lu, Yan Liu, Qiang Wang, and Huaxiang Zhang. 2019. “Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies.” Mathematical Problems in Engineering. doi:10.1155/2019/6943921.
    • Harvard:
      Yanyan Tan et al. (2019) ‘Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies’, Mathematical Problems in Engineering. doi: 10.1155/2019/6943921.
    • Harvard: Australian:
      Yanyan Tan, Xue Lu, Yan Liu, Qiang Wang & Huaxiang Zhang 2019, ‘Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies’, Mathematical Problems in Engineering, viewed 18 September 2019, .
    • MLA:
      Yanyan Tan, et al. “Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies.” Mathematical Problems in Engineering, 2019. EBSCOhost, doi:10.1155/2019/6943921.
    • Chicago/Turabian: Humanities:
      Yanyan Tan, Xue Lu, Yan Liu, Qiang Wang, and Huaxiang Zhang. “Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies.” Mathematical Problems in Engineering, 2019. doi:10.1155/2019/6943921.
    • Vancouver/ICMJE:
      Yanyan Tan, Xue Lu, Yan Liu, Qiang Wang, Huaxiang Zhang. Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies. Mathematical Problems in Engineering [Internet]. 2019 [cited 2019 Sep 18]; Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsdoj&AN=edsdoj.2d67917e69c6411c9dcfa46fc36342a9&custid=s8280428