Firefly algorithm: Difference between revisions

Revision as of 21:23, 14 January 2016

Revision as of 21:25, 14 January 2016

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* Deriving the sufficient and necessary conditions for the selections of control coefficients;

* Efficient strategies or mechanisms for the selections of the control parameters;

* Non-homogeneous update rules for enhancing the search ability<ref>http://godzilla.uchicago.edu/pages/ngaam/AdaFa/index.html</ref> was proposed in ref.<ref>{{cite journal |first=Ngaam J. |last=Cheung |first2=X.-M.|last2=Ding |first3=H.-B. |last3=Shen |title=Adaptive Firefly Algorithm: Parameter Analysis and its Application |journal=PLOS One |volume=9 |issue=11 |pages= e112634 |year=2014 |url=http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112634 |doi=10.1371/journal.pone.0112634}}</ref>.

Further, classical variants of the algorithm have unexpected parameter settings and limited update laws, notably the homogeneous rule needs to be improved in order to do more search on different fitness landscape. Ref. analyzes the trajectory of a single firefly in the traditional algorithm and an adaptive variant, respectively. These analyses lead to a general model of the algorithms including a set of the boundary conditions for the parameters guaranteeing the convergence tendencies of the two algorithms<ref>{{cite journal |first=Ngaam J. |last=Cheung |first2=X.-M.|last2=Ding |first3=H.-B. |last3=Shen |title=A Non-Homogeneous Firefly Algorithm and Its Convergence Analysis |journal=Journal of Optimization Theory and Applications |volume= |issue= |pages= |year=2016 |url=http://godzilla.uchicago.edu/pages/ngaam/NAdaFa/index.html |doi=10.1007/s10957-016-0875-4}}</ref>.