Discrete paired-bacteria optimizer for solving traveling salesman problem

Author

Li, M.S. ; Ji, T.Y. ; Wu, Q.H.

Author_Institution

Sch. of Electr. Power, South China Univ. of Technol. (SCUT), Guangzhou, China

fYear

2013

fDate

16-19 April 2013

Firstpage

86

Lastpage

91

Abstract

This paper focuses on implementing a Discrete Paired-Bacteria Optimizer (DPBO) to solve the Traveling Salesman Problem (TSP). As a well-studied NP-hard problem, it is known that the running time for any optimization algorithm for the TSP increases exponentially with the number of cities. Therefore, in order to reduce the optimization computational complexity, this research introduces a swarm algorithm inspired from the bacteria behavior. According to its performance on TSP benchmark cases, DPBO is able to solve the TSP problem with a superior advantage on time consumption.

Keywords

computational complexity; travelling salesman problems; DPBO; NP-hard problem; TSP; bacteria behavior; discrete paired-bacteria optimizer; optimization algorithm; optimization computational complexity; running time; swarm algorithm; time consumption; traveling salesman problem; Benchmark testing; Cities and towns; Convergence; Mathematical model; Microorganisms; Optimization; Sensors; Bacterial Behaviors; Optimization; Paired-Bacteria Optimizer; Traveling Salesman Problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence In Production And Logistics Systems (CIPLS), 2013 IEEE Workshop on

Conference_Location

Singapore

Type

conf

DOI

10.1109/CIPLS.2013.6595204

Filename

6595204