StoMADS algorithm for stochastic blackbox optimization

Implementation and comparison of SGD, SGD with momentum, RMSProp and AMSGrad optimizers on the Image classification task using MNIST dataset

Code for "Explainable Data-Driven Optimization" (ICML 2023)

Some sample codes for basic or complicated stochastic processes and simulations. Check the file names.

fireworks swarm optimization - efficient derivative free solver.

Slime Mold swarm optimization - efficient derivative free biologically inspired solver

Scripts and data used for the master's thesis "Portfolio selection with ES and regular vine copulae with EVT marginals" presented at the Wirtschaftsuniversität Wien in summer 2023. Code is structured for the purposes of the thesis and may not comply with best coding standards.

A stokhazesthai (stochastic) process, also called a random process, is one in which outcomes are uncertain (MAT 455, ISU).

a High-Performance Distributed Solver for Large-Scale Markov Decision Processes (MDP) relying on Inexact Policy Iteration; for Python and C++

Location & Distribution and Hydrothermal Coordination Models, using Stochastic Programming and Multicriteria Techniques, are proposed. Reports of the work in pdf and the GAMS code are included.

Unofficial PyTorch implementation of COCOB Backprop.

reading SMPS format files in C++ (Two-stage stochastic programs with fixed recourse)

Deep-Learning-Optimization-Algorithms-Streamlit-Application

Algorithm of selective averaging of coordinates (SAC)

A repository for studying predictive prescription using machine learning to model and solve stochastic problems.

Course of Stochastic Optimization in ISAE-SUPAERO

Source code for Mathematical Modelling Assignment

The goal of this project is to build a simulation model to determine the largest expected revenue from an electric vehicle charging station in a one month time period given the storage capacity, charging grid change costs, demand and supply.

A Python package that includes various stochastic algorithms.

This repository is a collaborative effort to compile, implement, and share solutions to a diverse range of problems in Operations Research (OR), Mathematical Optimization, Supply Chain Analytics, and Artificial Intelligence (AI). By gathering algorithms, ideas, and solutions from various sources—including original work, research papers, and books.