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Fireworks algorithm

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This is an old revision of this page, as edited by Cjp419 (talk | contribs) at 21:20, 8 February 2020 (Added a new algorithm description section, a brief elaboration on the summary, and a reference to the paper.). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

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]


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  1. ^ Tan, T; Zhu, Y (2010), Fireworks algorithm for optimization, International Conference in Swarm Intelligence {{citation}}: Invalid |display-authors=2 (help)
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