Title :
An Algorithm in Solving the TSP Based on the Improved Genetic Algorithm
Author :
Ma Fangfang ; Li Han
Author_Institution :
Fundamental Dept., Shandong Univ. of Sci. & Technol., Tai´an, China
Abstract :
The Traveling Salesman Problem is a famous NP - complete problem in Graph and Combinatorial Optimization. This article, proposed an improved genetic algorithm in solving the multi-constrained Traveling Salesman Problem. First of all, increase constraint conditions of the Traveling Salesman Problem, including time, area and cost constraint, at the same time design the fitness function which describes the merit of the line. Then use vertices to encode the traveling path and use the improved genetic algorithm to search the optimal path. Finally, under the condition that do not consider the region constraint, by using the obtained set of the path to get a better delineation of areas.
Keywords :
genetic algorithms; travelling salesman problems; NP complete problem; combinatorial optimization; genetic algorithm; graph optimization; traveling salesman problem; Cities and towns; Constraint optimization; Cost function; Evolution (biology); Genetic algorithms; Genetic engineering; Information science; Promotion - marketing; Time factors; Traveling salesman problems;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.231