Multi-stage Stochastic Programming for Integrated Network Optimization in Hurricane Relief Logistics and Evacuation Planning

[ToN 2024] On the Benefits of Traffic “Reprofiling” the Multiple Hops Case—Part I

Formulate the network optimization problem as a discrete model, identifying mathematically the variables and constraints associated with the network. Formulate (mathematically) and solve a non-linear optimization problem based on real (or realistic) world data.

Network Optimization C++ Code

Optimal placement of police cars to minimize response time to events in police districts.

TravelPathOptimizer for trucking logistics is a software tool that boosts efficiency by determining optimal routes through algorithms. It accounts for traffic, weather, load, and timing, dynamically adjusting for delays. This reduces costs, ensures prompt deliveries, and enhances service, boosting trucking productivity and sustainability.

A brief course intended to introduce non-programmers to python and data wrangling. Also, demonstration of network optimization, pdf creation in Python, and a simple Monte Carlo simulation.

A simple guide to optimize your ping in CS2 through Windows Registry tweaks and in-game settings adjustments by @OhLasFar on Twitter.

Laboratory sessions for the class "Optimization & Analytics". Grade 9.7/10 (Honours)

🔍To choose the best CloudFront IPs for achieving fast and low-latency connections

Network Optimisation solver

Network-flows: a c++ command line tool for network optimization problems

This repository contains solution to the "DDAP/DAP solved with evolutionary algorithm" project of the course "OAST - Optimization and Analysis of ICT networks" realized during the winter semester of 2022 on the Warsaw University of Technology.

This advanced and complex project implements an AI-powered optimization system for 5G Open RAN networks. Using machine learning and deep learning, the system optimizes network performance by detecting anomalies, predicting network traffic, and dynamically allocating resources.

Master's Thesis: Dynamic Quality Estimation of Wireless Links with Autonomous Agents

A variant of neuroplan that uses synthesized datasets (based on the Topology Zoo)

Maximize the flow of data through a network with this efficient Maximum Flow Algorithm implemented in Kotlin. Use it to optimize data transmission and improve network performance.

GPU implementation of Floyd-Warshall and R-Kleene algorithms to solve the All-Pairs-Shortest-Paths(APSP) problem on Graphs. Code includes random graph generators and benchmarking/plotting scripts.

Find maximum possible flow in your graphs, optimize networks.

In this project, I built several optimization models to determine production level, manage shipment, and maximize thesis points. I also built queueing models to analyze queueing systems in a hospital and made recommendations to meet the criteria, and simulation models to analyze system performance under uncertainty.