Thesis Details
Aplikace mravenčích algoritmů v rozsáhlých úlohách TSP
Currently, many applications place emphasis on finding the optimal solution to a particular problem. However, it is typical for some tasks that their complexity increases exponentially depending on the size of the instance. A typical example of such a problem is the Traveling Salesman Problem (TSP). One class of methods that have proven to be very helpful in solving TSPs are ant algorithms. Nonetheless, they reached their limit - a high number of cities in the instance and became almost unusable due to time and memory requirements. This bachelor thesis aims to modify the ant algorithm and create a system capable of quickly and efficiently solve large-scale TSPs without significant loss in the quality of the solution found. Optimization will focus on reducing memory complexity and total execution time.
Ant Colony Optimization, Travelling Salesman Problem, large-scale TSP instances, MAX-MIN Ant System
Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D. (DITS FIT BUT), člen
Grézl František, Ing., Ph.D. (DCGM FIT BUT), člen
Hrubý Martin, Ing., Ph.D. (DITS FIT BUT), člen
Polčák Libor, Ing., Ph.D. (DIFS FIT BUT), člen
@bachelorsthesis{FITBT22589, author = "Patr\'{i}cia Ramosov\'{a}", type = "Bachelor's thesis", title = "Aplikace mraven\v{c}\'{i}ch algoritm\r{u} v rozs\'{a}hl\'{y}ch \'{u}loh\'{a}ch TSP", school = "Brno University of Technology, Faculty of Information Technology", year = 2020, location = "Brno, CZ", language = "slovak", url = "https://www.fit.vut.cz/study/thesis/22589/" }