Learning 2-opt Heuristics for the TSP via Deep Reinforcement Learning

GraphLab is an application that shows visually how several graph algorithms work

How to solve the traveling salesman problem with the 2-opt algorithm, a fast heuristic search algorithm.

Implementation of the paper A Genetic Algorithm for a Green Vehicle Routing Problem

Java 2-opt solution for TSP Coursework

The research work on local search algorithms

The travelling salesman problem (TSP) asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?

A Travelling Salesman Problem (TSP) solver using a hybrid of strategies

Competitive C++ solution to the Travelling Salesperson 2D problem, that includes the implementation of 6 algorithms: greedy, Clarke-Wright, Christofides, 2-opt, 3-opt, and Lin-Kernighan (k-opt). Done as part of the project assignment in the *DD22440 Advanced Algorithms* course at KTH, by Prof. Danupon Nanongkai.

A simple Quadratic Assignment Problem solver using heuristics and metaheuristics

A Python package for visualizing graph algorithms.

Vehicle Routing Problem solver with cargo compatibility constraints. Interactive web UI, 2-opt/3-opt optimization, Excel export.

Vehicle Routing Problem optimization with Genetic Algorithm

Multi-storey Vehicle Routing Problem optimization using Iterated Local Search

Podium at Artificial Intelligence Cup 2022 - USI

TSP optimization, Operations Research 2 project, UniPD 2022/23

Fully automated, constraint-driven solution to the NP-hard TSP, featuring dynamic package loading with no hardcoded logic. Handles deadlines, groupings, delays, and truck constraints using a multi-phase optimization strategy that minimizes distance while meeting all delivery requirements.

Algorithms Project for Oregon State University

Assignments of Artificial Intelligence Sessional Course CSE 318 in Level-3, Term-2 of CSE, BUET