OptiMIClass
Automatic n-dimensional data clustering tool powered by five advanced
This software is an automatic n-dimensional quantitative data clustering tool based on five optimization heuristics (GA, PSO, ACO, SA, and TS). It enables performance comparisons across heuristics and parameter testing within each method, analyzing solution quality, runtime, and convergence; it also includes a repository of benchmark test tables and an intuitive interface for research and operational use.
It was developed by M.Sc. Jeffry Chavarría-Molina and M.Sc. Juan José Fallas-Monge at the Instituto Tecnológico de Costa Rica (TEC), School of Mathematics, with support from the Vice-Rectory for Research and Extension (VIE). The software was a direct outcome of “Combinatorial optimization heuristics for data classification” (Code: 5402-1440-3901), and its development continued within the related project “Disease propagation: heuristics applied to optimizing control measures” (Code: 540114404201).