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    Dynamic Behavior Analysis of Membrane-Inspired Evolutionary Algorithms

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    Publication date
    2014
    Author
    Zhang, G.
    Cheng, J.X.
    Gheorghe, Marian
    Keyword
    Membrane computing
    ; Membrane-inspired evolutionary algorithm
    ; Dynamic behavior
    ; Quantum-inspired evolutionary algorithm
    ; Knapsack problem
    ; Tissue p systems
    ; Differential evolution
    ; Optimization problems
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    A membrane-inspired evolutionary algorithm (MIEA) is a successful instance of a model linking membrane computing and evolutionary algorithms. This paper proposes the analysis of dynamic behaviors of MIEAs by introducing a set of population diversity and convergence measures. This is the first attempt to obtain additional insights into the search capabilities of MIEAs. The analysis is performed on the MIEA, QEPS (a quantum-inspired evolutionary algorithm based on membrane computing), and its counterpart algorithm, QIEA (a quantum-inspired evolutionary algorithm), using a comparative approach in an experimental context to better understand their characteristics and performances. Also the relationship between these measures and fitness is analyzed by presenting a tendency correlation coefficient to evaluate the importance of various population and convergence measures, which is beneficial to further improvements of MIEAs. Results show that QEPS can achieve better balance between convergence and diversity than QIEA, which indicates QEPS has a stronger capacity of balancing exploration and exploitation than QIEA in order to prevent premature convergence that might occur. Experiments utilizing knapsack problems support the above made statement.
    URI
    http://hdl.handle.net/10454/10829
    Version
    No full-text in the repository
    Citation
    Zhang GX, Cheng JX and Gheorghe M (2014) Dynamic Behavior Analysis of Membrane-Inspired Evolutionary Algorithms. International Journal of Computers Communications & Control. 9(2): 227-242.
    Link to publisher’s version
    http://dx.doi.org/10.15837/ijccc.2014.2.794
    Type
    Article
    Collections
    Engineering and Informatics Publications

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