This repository contains the work I completed during the Prescriptive Analytics seminar at Dresden University of Technology. The primary focus of the seminar was to solve optimization problems using a solver architecture.
As part of the course, we explored a variety of optimization problems and learned to implement solutions using different optimization techniques. For my exam, I tackled the Orienteering Problem, a well-known problem in the field of combinatorial optimization. I used the Variable Neighborhood Search (VNS) metaheuristic to develop an efficient solution to the problem.
The Orienteering Problem involves finding the most efficient route through a set of locations, with the goal of maximizing the total score obtained by visiting selected locations, while staying within a given time or distance constraint. The challenge lies in balancing the trade-off between visiting high-value locations and completing the route within the allowed limit.
Variable Neighborhood Search (VNS) is a metaheuristic algorithm designed to escape local optima by systematically changing the neighborhood structures during the search process. By exploring increasingly distant neighborhoods, VNS enhances the chances of finding a global optimum.