Fireworks algorithm: Difference between revisions
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Added a new algorithm description section, a brief elaboration on the summary, and a reference to the paper. |
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The '''Fireworks Algorithm (FWA)''' is a [[swarm intelligence]] algorithm that explores a very large solution space by choosing a set of random points confined by some distance metric in the hopes that one or more of them will yield promising results, allowing for a more concentrated search nearby. |
The '''Fireworks Algorithm (FWA)''' is a [[swarm intelligence]] algorithm that explores a very large solution space by choosing a set of random points confined by some distance metric in the hopes that one or more of them will yield promising results, allowing for a more concentrated search nearby. |
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== Algorithm Description == |
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The algorithm is implemented and described in terms of the explosion process of fireworks: explosions occur at specific points, and "sparks" fan out from the explosion. Each spark location is considered until an adequately optimal point is found. In terms of optimization, when finding an <math>x_j</math> satisfying <math>f(x_j)=y</math>, the algorithm continues until a spark is sufficiently near <math>x_j</math>.<ref>{{Citation | last1 = Tan | first1 = T | last2 = Zhu | first2 = Y | display-authors = 2 | title = Fireworks algorithm for optimization | year = 2010 | publisher = International Conference in Swarm Intelligence }}</ref> |
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==External links== |
==External links== |
Revision as of 21:20, 8 February 2020
The Fireworks Algorithm (FWA) is a swarm intelligence algorithm that explores a very large solution space by choosing a set of random points confined by some distance metric in the hopes that one or more of them will yield promising results, allowing for a more concentrated search nearby.
Algorithm Description
The algorithm is implemented and described in terms of the explosion process of fireworks: explosions occur at specific points, and "sparks" fan out from the explosion. Each spark location is considered until an adequately optimal point is found. In terms of optimization, when finding an satisfying , the algorithm continues until a spark is sufficiently near .[1]