Overview

Traveling Salesman Problem Solver is a desktop educational application designed for solving and visualizing the Traveling Salesman Problem (TSP).

The application combines optimization algorithms, matrix-based input, graphical route visualization, and explanatory textual output inside a standalone Windows desktop interface.

The project was created as an educational and demonstration-oriented utility focused on algorithm visualization, validation, and readability of the solving process.

Context

The goal of the project was to create a desktop utility capable of:

• solving Traveling Salesman Problem scenarios;
• validating matrix-based distance data;
• visualizing calculated routes;
• demonstrating optimization algorithms;
• providing readable educational explanations of the solving process.

The application was intended for coursework, algorithm demonstrations, and educational scenarios related to optimization and graph-based problems.

Responsibilities

My responsibilities included:

• application architecture;
• implementation of TSP algorithms;
• GUI development;
• matrix handling logic;
• validation system;
• route visualization;
• formatted educational output;
• optimization workflow design.

Solution

The solution was implemented as a WPF desktop application using .NET 8 and standard platform libraries.

The application allows users to:

• generate and edit distance matrices;
• select a starting city;
• calculate optimized routes;
• visualize the resulting path;
• review intermediate algorithm steps and calculations.

The system supports both:

• brute-force search for smaller datasets;
• heuristic nearest-neighbor approach for larger city counts.

The interface was designed to remain educational and visually understandable while handling matrix-based optimization tasks.

Technical Details

Stack

• C#
• .NET 8
• WPF
• System.Data

Architecture

The project separates:

• matrix parsing and validation;
• optimization algorithms;
• route visualization;
• result formatting;
• GUI interaction logic.

Dedicated models are used for:

• problem definition;
• result representation;
• solver isolation from the UI layer.

Functionality

Implemented functionality includes:

• editable distance matrices;
• symmetric random demo matrix generation;
• validation of matrix correctness;
• brute-force TSP solving for smaller datasets;
• nearest-neighbor heuristic solving for larger datasets;
• route length calculation;
• textual step-by-step logs;
• circular route visualization using Canvas rendering.

The visualization layer illustrates the calculated route between cities and helps users understand algorithm behavior.

Challenges

The main challenges included:

• balancing algorithmic complexity with desktop application responsiveness;
• validating large matrix datasets safely;
• visualizing routes inside a lightweight educational interface;
• separating exact and heuristic solving approaches clearly for users;
• keeping the UI readable while presenting optimization logs and visual output simultaneously.

Result

The final application successfully demonstrated:

• structured WPF desktop application architecture;
• implementation of optimization and graph algorithms;
• matrix-based data processing;
• graphical route visualization;
• educational presentation of algorithm workflows;
• separation of computational logic and UI components.

The project also served as a reusable example of combining optimization algorithms, visualization, and desktop GUI development in .NET.

Media

The gallery contains:

• matrix input examples;
• route visualization previews;
• optimization result logs and algorithm output.

Notes

• Educational/demo-oriented project.
• Ukrainian-language interface.
• Uses brute-force and heuristic approaches depending on dataset size.
• Implemented without third-party dependencies.