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The future of optimization is now being
conquered by modern meta-heuristic algorithms.
Genetic algorithms, differential evolution, harmony
search, firefly algorithm and cuckoo search are such
meta-heuristic algorithms which have marked their
success over many optimization tasks. Simplicity of the
algorithm, less memory consumption and the accuracy
of the approximations can be stated as the major
reasons for their popularity. In this article, we are
presenting a software solution that proposes some
modifications to the existing firefly algorithm. The
modification; archived firefly algorithm [AFFA]
exhibits the ability of finding almost all the real and
complex roots of a given nonlinear equation within a
reasonable range. The software implementation
includes two main properties; an archive to collect the
better fireflies and a flag to determine poor
performance in firefly generations. The new
modification is tested over Genetic algorithms (GA), a
phenomenal in the field of nature inspired algorithms
and also with a modified GA embedded with same
properties the AFFA has. A simple GUI is developed
using Matlab GUIDE to present the findings. Computer
simulations show that the AFFA performs well in
solving nonlinear equations with real and complex roots
within a specified region. The suggested method can be
further extended to solve a given system of nonlinear
equations.
