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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 3 Issue 7, 2012.
Abstract: The Traveling salesman problem (TSP) is to find a tour of a given number of cities (visiting each city exactly once) where the length of this tour is minimized. Testing every possibility for an N city tour would be N! Math additions. Genetic algorithms (GA) and Memetic algorithms (MA) are a relatively new optimization technique which can be applied to various problems, including those that are NPhard. The technique does not ensure an optimal solution, however it usually gives good approximations in a reasonable amount of time. They, therefore, would be good algorithms to try on the traveling salesman problem, one of the most famous NP-hard problems. In this paper I have proposed a algorithm to solve TSP using Genetic algorithms (GA) and Memetic algorithms (MA) with the crossover operator Edge Assembly Crossover (EAX) and also analyzed the result on different parameter like group size and mutation percentage and compared the result with other solutions.
Mohd. Junedul Haque and Khalid. W. Magld, “Improving the Solution of Traveling Salesman Problem Using Genetic, Memetic Algorithm and Edge assembly Crossover” International Journal of Advanced Computer Science and Applications(IJACSA), 3(7), 2012. http://dx.doi.org/10.14569/IJACSA.2012.030715
@article{Haque2012,
title = {Improving the Solution of Traveling Salesman Problem Using Genetic, Memetic Algorithm and Edge assembly Crossover},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2012.030715},
url = {http://dx.doi.org/10.14569/IJACSA.2012.030715},
year = {2012},
publisher = {The Science and Information Organization},
volume = {3},
number = {7},
author = {Mohd. Junedul Haque and Khalid. W. Magld}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.