Estimation of cost rate percentage for travelling salesman problem using hybridized ACO algorithm

• Published in: ICRAIE : 2016 International Conference on Recent Advances and Innovations in Engineering : 23-25 December 2016 pp. 1 - 6
• Main Authors: Jaiswal, Kratika, Nagar, Shirish
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2016
• Subjects: Ant colony optimization; Chebyshev approximation; chebyshev distance; Classification algorithms; Cost rate percentage; Euclidean distance; Hamming distance; Mathematical model; mRAR-algorithm; Optimization
• ISSN: 5090-2806
• DOI: 10.1109/ICRAIE.2016.7939533

Cost rate percentage is a percentage that suggests reducing the cost of path that is traveled by salesman from one city to another. Ant colony optimization (ACO) is an algorithm that is used to determine the shortest path and best cost at minimum iterations possible for a random data set on the basis of Euclidean distance formula. In this paper we have presented ACO algorithm with certain modifications as we have introduce equations like hamming, chebyshev along with standard Euclidean equation inside the ACO algorithm. The proposed algorithm is applied over the random data set generated by the code itself in Matlab tool. A proposed algorithm when depicts the rate percentage, it actually considers the surroundings and the history of that particular subject. ACO gives the best cost and covers the whole data set with minimum cost and shortest path.