  Evolutionary Multi-Objective Optimization is becoming a hot research area and
quite a few papers regarding these algorithms have been published. However the
role of local search techniques has not been expanded adequately. This paper
studies the role of a local search technique called 2-opt for the
Multi-Objective Travelling Salesman Problem (MOTSP). A new mutation operator
called Jumping Gene (JG) is also used. Since 2-opt operator was intended for
the single objective TSP, its domain has been expanded to MOTSP in this paper.
This new technique is applied to the list of KroAB100 cities.
