Implémentation JAVA Gradient à pas fixe

This project is about using artificial intelligence and parallel processing power to solve a difficult task scheduling problem

Eclipse-based tool for optimal configuration of software product lines

Hashcode 2017 - Google algorithm competition

Project for compressing bitmap images

Solves the discrete, single-machine, multi-item, single-level lot sizing problem via graph algorithms

Multi-Objective Continuous Optimisation Problems

Distributed Information System that manages operations, generates its optimal schedule, evaluates its metrics, tracks all activity in real-time, provides chat room, sends notifications.

Information system that manages operations, generates its optimal schedule, evaluates its metrics, tracks events in real-time, provides instant messaging, sends notifications

Solution aux exercices Mars Lander 2 & 3 proposés par la plateforme Codingame.

Analysis of market data in context of optimising SBE-Aeron stack

The simulated annealing algorithm started with a random route and got a random number for the route. When the number is smaller and equal to the probability function, it will proceed to the adjacent route. If the adjoining route is larger than the current route, it will still proceed to the next route until it gets the shortest adjacent route. I…

A tool designed for the simulation of mobile network technologies, specifically 3G and 4G, facilitating the planning, sizing, and optimization of network resources

The nearest neighbor algorithm gets the shortest route from the initial course whenever generating the result. It will always check for the journey to reduce one city from the way, which is the shortest route, and then it will run again for the remaining cities until it gets the best result. It follows the pattern until there are no remaining ci…

This project is for the courseworks of Cambridge Engineering Module 4M17 - practical optimisation.

In the brute force algorithm, the program will go through all the permutations of starting a trip from one of the cities, visiting each city once, and returning to the first cities. It shows all the possible shortest routes with the same distance out of all the permutations. The downside of this algorithm is that increasing the number of cities …

In implementing the hill-climbing algorithm, the program first generated a distance based on the result, and it will loop back to previous routes. Then as it connects back, the next course swaps randomly two cities, and it loops again for the shortest path. It will stay on the same route for more iteration until it reaches the shortest path. The…

LagAssist source code, but with gradle.

University Coursework @ UCL for compilers ( COMP0012 / COMP0207 ) module for backend code optimization of code using BCEL

In implementing the ant colony optimization algorithm, the developer has used 500 ants and 8 US-based cities to calculate the shortest route for the TSP. The developer found out that the number of ants does not affect finding the shortest route. They also observed that the number of cities does not increase the time to calculate the shortest rou…