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

fYear

2010

fDate

15-16 May 2010

Firstpage

239

Lastpage

241

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/WMSVM.2010.67

Filename

5558311