ACS Applied Computer Science

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FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS

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Modern real world science and engineering problems can be classified as multi-objective optimisation problems which demand for expedient and efficient stochastic algorithms to respond to the optimization needs. This paper presents an object-oriented software application that implements a firework optimization algorithm for function optimization problems. The algorithm, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard benchmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended experimentation. Additionally, this paper validates the effect of runtime on the algorithm performance.
  • APA 6th style
Baidoo, E. (2017). Fireworks algorithm for unconstrained function optimization problems. Applied Computer Science, 13(1), 61-74. doi:10.23743/acs-2017-06
  • Chicago style
Baidoo, Evans. "Fireworks Algorithm for Unconstrained Function Optimization Problems." Applied Computer Science 13, no. 1 (2017): 61-74.
  • IEEE style
E. Baidoo, "Fireworks algorithm for unconstrained function optimization problems," Applied Computer Science, vol. 13, no. 1, pp. 61-74, 2017.
  • Vancouver style
Baidoo E. Fireworks algorithm for unconstrained function optimization problems. Applied Computer Science. 2017;13(1):61-74.
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