Title :
Comparative analysis of two different ant colony algorithm for model of TSP
Author :
Joshi, Sourabh ; Kaur, Sarabjit
Author_Institution :
Dept. Comput. Sci. Eng., CT Inst. of Technol. & Res., Jalandhar, India
Abstract :
Travelling Salesman Problem is well - known and extensively studied problem which plays an important role in combinatorial optimization and in context of ACO. Ant Colony Optimization is heuristic Algorithm which was initially applied on TSP and is an advance technique applied on various other optimization problems. In the research we study two different kinds of Ant Colony algorithms named as Ant System and the improved version of Ant system known as Max-Min Ant System performed in MATLAB to solve travelling Salesman Problem and their respective results are shown by using graphical implementation. In this paper both systems are analyzed by solving the same example of TSP and depict which system solve the problem efficiently with respect to cost and time.
Keywords :
ant colony optimisation; combinatorial mathematics; minimax techniques; travelling salesman problems; ACO; MATLAB; TSP; ant colony algorithm; combinatorial optimization; graphical implementation; heuristic algorithm; max-min ant system; travelling salesman problem; Algorithm design and analysis; Ant colony optimization; Cities and towns; Computers; MATLAB; Mathematical model; Optimization; Ant Colony Optimization; Ant System; Max-Min Ant System; Travelling Salesman Problem;
Conference_Titel :
Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in
Conference_Location :
Ghaziabad
DOI :
10.1109/ICACEA.2015.7164775
