Genetic Algorithms for DTSP: A Study of Different Mutation Rates

Abstract

ABSTRACT
This paper deals with performance evaluation of genetic algorithms (GAs) for the dynamic traveling salesman problem (DTSP) using different values of mutation rates. DTSP is known to be NP-hard, and consists of the solution containing N! permutations. The objective of the study is to evaluate the ability of GA to solve the optimization problems using some variations in its parameters. All performance evaluation has been performed using a software program developed in the Matlab environment. The results clearly suggest that different settings of parameters like mutation operator can give us better solutions than using static parameter settings. GA clearly demonstrates good results for DTSP with different values of mutation rates.

Keywords: Genetic algorithms, traveling salesman problem, genetic operators, pseudo-code