Particles swarm optimization-simulated annealing (PSO-SA) with mass extinction applied to nonlinear optimization problems /

Jopson, Maria Andrea Aizza Galon.

Particles swarm optimization-simulated annealing (PSO-SA) with mass extinction applied to nonlinear optimization problems / Maria Andrea Aizza Galon Jopson. - 2009 - 83 leaves.

Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2009

Particle Swarm Optimization ? Simulated Annealing (PSO-SA) with Mass Extinction is an extension of Xie's et.al.?s (2002), which searches for a hybrid technique that will get an optimal solution in numerical problems in evolutionary optimization research. PSO-SA with Mass Extinction is a combination of heuristic, meta-heuristic and evolutionary algorithms that aims to solve underlying problems in solving underlying problems in solving evolutionary problems. This hybrid algorithm will be tested three benchmark evolutionary functions namely; Rosenbrock function, Rastrigin function and Griewank function.


Optimization.
Particle Swarm Optimization-Simulated Annealing (PSO-SA)
Simulated annealing.


Undergraduate Thesis --CMSC200,
 
University of the Philippines Mindanao
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