The Ant Colony Optimization belongs into the metaheuristic methods category and it has been developing quite recently. So far it has shown its capabalities to over-perform other metaheuristic methods in quality of the solutions. This work brings analysis of the possible applications of the method on the classical optimization combinatorial problems -- traveling salesman problem, vehicle routing problem, knapsack problem, generalized assignment problem and maximal clique problem. It also deals with the practical experiments with application on several optimization problems and analysis of the time and memory complexity of such algorithms. The last part of the work is dedicated to the possibility of parallelization of the algorithm, which was result of the application of the ACO method on the traveling salesman problem. It brings analysis of the crucial operations and data synchronization issues, as well as practical example and demonstration of the parallelized version of the algorithm.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:76766 |
Date | January 2005 |
Creators | Chu, Andrej |
Contributors | Jablonský, Josef, Janáček, Jaroslav, Linda, Bohdan |
Publisher | Vysoká škola ekonomická v Praze |
Source Sets | Czech ETDs |
Language | Slovak |
Detected Language | English |
Type | info:eu-repo/semantics/doctoralThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.1187 seconds