Implementations of several metaheuristics in Python
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Updated
Jul 31, 2025 - Python
Implementations of several metaheuristics in Python
This repository contains the source code and documentation for the OptiNumPy library, a numerical analysis optimization package written in Python. The library provides various numerical optimization algorithms for solving optimization problems.
Comprehensive technology map categorizing trends and use cases in Gen AI and Spatial Computing
Web Site Optimization: Speed Up Your Site website
An application for visualizing and comparing the work of multidimensional optimization methods with using derivative of the objective function: Gradient Descent Method, Newton Method, Fletcher-Reeves Method.
Adaptive Trust Region Methods
Explore Optimization
FinDi: Finite Difference Gradient Descent can optimize any function, including the ones without analytic form, by employing finite difference numerical differentiation within a gradient descent algorithm
multiple pages used for various page optimization assignments of udacity's frontend nanodegree program
Data structures and algorithms project done in the 3rd semester
the knapsack problem and the subset sum problem (NP-Hard Problem)
16 optimizing insights on ensemble learning with Python.
A C# SDK for interacting with the globalMOO API, providing a simple and intuitive interface for optimization tasks.
This code performs transport separation with the help of optimization with Tensors
A priori lexicographic multi-objective optimization. 🍎🐮
Условная оптимизация (не выпуклый случай). Проверка условий теоремы Каруша-Куна-Таккера.
Julia implementations of various animal-inspired optimizers
On the Optimal Use of Metamodel-Assisted Evolutionary Algorithms in Aerodynamic Applications
★Math researches and algorithms★
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