A novel memetic genetic algorithm for solving traveling salesman problem based on multi-parent crossover technique

Arindam Roy; Apurba Manna; Samir Maity

doi:10.31181/dmame1902076r

Authors

Arindam Roy Deptartment of Computer Science, Prabhat Kumar College, Purba Medinipur, West Bengal, India
Apurba Manna Deptartment of Computer Science, Prabhat Kumar College, Purba Medinipur, West Bengal, India
Samir Maity Operations Management Group, Indian Institute of Management, Kolkata, India

DOI:

https://doi.org/10.31181/dmame1902076r

Keywords:

TSP, Memetic GA, multi-parent crossover.

Abstract

In the present study, a Novel Memetic Genetic Algorithm (NMGA) is developed to solve the Traveling Salesman Problem (TSP). The proposed NMGA is the combination of Boltzmann probability selection and a multi-parent crossover technique with known random mutation. In the proposed multi-parent crossover parents and common crossing point are selected randomly. After comparing the cost/distance with the adjacent nodes (genes) of participated parents, two offspring’s are produced. To establish the efficiency of the developed algorithm standard benchmarks are solved from TSPLIB against classical genetic algorithm (GA) and the fruitfulness of the proposed algorithm is recognized. Some statistical test has been done and the parameters are studied.

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