Title :
Innovative Genetic Algorithm for Solving GTSP
Author :
Zhao, Xi ; Zhu, Xiao-Ping
Author_Institution :
Coll. of Comput. Sci. & Eng., Guangdong Inst. of Sci. & Technol., Zhuhai, China
Abstract :
There are two kinds of Generalized Traveling Salesman Problems (GTSP) corresponding to the different restraint conditions, which the cost functions satisfy. This study aims at solving a special case of the second kind of GTSP, where the triangular inequality constraint still remains valid for the edge costs within districts. An innovative genetic algorithm using generalized chromosomes with void vertices is employed to solve the special GTSP. Case study of simulation for benchmark test problems shows that the proposed algorithm is considerably successful.
Keywords :
genetic algorithms; travelling salesman problems; GTSP; benchmark test problems; cost functions; edge costs; generalized chromosomes; generalized traveling salesman problems; innovative genetic algorithm; restraint conditions; triangular inequality constraint; void vertices; Algorithm design and analysis; Biological cells; Cost function; Decoding; Genetic algorithms; Heuristic algorithms; Traveling salesman problems; GA; GTSP; Generalized chromosome; Void vertex;
Conference_Titel :
Modeling, Simulation and Visualization Methods (WMSVM), 2010 Second International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-7077-8
Electronic_ISBN :
978-1-4244-7078-5
DOI :
10.1109/WMSVM.2010.67
