Optimization of real-world supply routes by nature-inspired metaheuristics

The traveling salesman problem (TSP) is an iconic permutation problem with a number of applications in planning, scheduling, and logistics. It has also attracted much attention as a benchmarking problem frequently used to assess the properties of a variety of nature-inspired optimization methods. However, the standard libraries of TSP instances, such as the TSPLIB, are often decades old and might not reflect the requirements of modern real-world applications very well. In this work, we introduce several novel TSP instances representing real-world locations of pharmacies in several major cities of the Czech Republic. We look for the optimum routes between the pharmacies by selected nature-inspired algorithms and compare the results obtained on the real-world instances with their results on standard TSPLIB instances.