FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS
Copyright policy )FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS
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.
Natural computing, Swarm intelligence, Fireworks algorithm, Function optimization, Information technology, Artificial Intelligence, 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, FOS: Mathematics, Firefly Algorithm, Swarm Intelligence Optimization Algorithms, Optimization problem, this paper validates the effect of runtime on the algorithm performance., Global Optimization, Geography, Multi-Objective Optimization, Optimization Applications, Mathematical optimization, Mathematical programming, QA75.5-76.95, T58.5-58.64, Computer science, Programming language, Algorithm, Computational Theory and Mathematics, Particle Swarm Optimization, Electronic computers. Computer science, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Benchmark (surveying), Multiobjective Optimization in Evolutionary Algorithms, Java, Software, Mathematics, Geodesy
Natural computing, Swarm intelligence, Fireworks algorithm, Function optimization, Information technology, Artificial Intelligence, 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, FOS: Mathematics, Firefly Algorithm, Swarm Intelligence Optimization Algorithms, Optimization problem, this paper validates the effect of runtime on the algorithm performance., Global Optimization, Geography, Multi-Objective Optimization, Optimization Applications, Mathematical optimization, Mathematical programming, QA75.5-76.95, T58.5-58.64, Computer science, Programming language, Algorithm, Computational Theory and Mathematics, Particle Swarm Optimization, Electronic computers. Computer science, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Benchmark (surveying), Multiobjective Optimization in Evolutionary Algorithms, Java, Software, Mathematics, Geodesy
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