Discrete paired-bacteria optimizer for solving traveling salesman problem

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.