Hybridizing PSM and RSM Operator for Solving NP-Complete Problems: Application to Travelling Salesman Problem
This is an incremental improvement for solving NP-complete problems like TSP using genetic algorithms.
The authors tackled the Traveling Salesman Problem by developing a new hybrid mutation operator (HPRM) for genetic algorithms, which outperformed existing operators like RSM and PSM on the BERLIN52 instance.
In this paper, we present a new mutation operator, Hybrid Mutation (HPRM), for a genetic algorithm that generates high quality solutions to the Traveling Salesman Problem (TSP). The Hybrid Mutation operator constructs an offspring from a pair of parents by hybridizing two mutation operators, PSM and RSM. The efficiency of the HPRM is compared as against some existing mutation operators; namely, Reverse Sequence Mutation (RSM) and Partial Shuffle Mutation (PSM) for BERLIN52 as instance of TSPLIB. Experimental results show that the new mutation operator is better than the RSM and PSM.