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The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation net…
Morph an input dataset of 2D points into select shapes, while preserving the summary statistics to a given number of decimal points through simulated annealing. It is intended to be used as a teaching tool to illustrate the importance of data visualization.
This repository demonstrates how the Presentation Scheduling problem, which is analogous to the famous University Course Timetabling Problem (UCTP), can be solved using the Hybrid Genetic Algorithm-Simulated Annealing (HGASA) algorithm.
Resource allocation using optimization algorithms and python. Assigning the right resources with the right skills to specific projects or activities with certain requirements.
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.