—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.
—Genetic algorithm, multi-objective, jumping gene, travelling salesman problem
Rohan Agrawal, was with the JIIT Noida, India. He is now with the Department of CS, Columbia University, USA (e-mail: email@example.com).
Cite:Rohan Agrawal, "Application of the Modified 2-OPT and Jumping Gene Operators in Multi-Objective Genetic Algorithm to Solve MOTSP," Journal of Advances in Computer Networks vol. 1, no. 4, pp. 320-322, 2013.