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Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.
Implementation of Genetic Algorithm, Memetic Algorithm and Constraint Satisfaction on a Time Table scheduling problem. Also has an implementation of MiniMax Strategy for TicTacToe
This work was aimed at finding methods to identify the most distant proteins and most diverse subsets of proteins from large protein databases in a scalable and efficient way using a dataset of protein embeddings from SwissProt, data mining techniques and metaheuristics.