Title :
An efficient ant colony system for solving the new Generalized Traveling Salesman Problem
Author_Institution :
Key Lab. of Numerical Simulation of Sichuan Province, Neijiang Normal Univ., Neijiang, China
Abstract :
The Generalized Traveling Salesman Problem (GTSP) is an extension of the classical traveling salesman problem and has many interesting applications. In this paper we present a New Generalized Traveling Salesman Problem (NGTSP), and the current GTSP is only a special case of the NGTSP. To solve effectively the NGTSP, we extend the ant colony system method from TSP to NGTSP. Meanwhile, to improve the quality of solution, a local searching technique is introduced into this method to speed up the convergence, and a novel parameter adaptive technique is also introduced into this method to avoid locking into local minima. Experimental results on numerous TSPlib instances show that the proposed method can deal with the NGTSP problems fairly well, and the developed improvement techniques is significantly effective.
Keywords :
optimisation; search problems; travelling salesman problems; ant colony system; local searching technique; new generalized traveling salesman problem; parameter adaptive technique; Algorithm design and analysis; Clustering algorithms; Convergence; Genetic algorithms; Numerical simulation; Partitioning algorithms; Traveling salesman problems; ACS; GTSP; NGTSP; parameter adaptive;
Conference_Titel :
Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-61284-203-5
DOI :
10.1109/CCIS.2011.6045099