Developing a Java-based Genetic Algorithm to Solve the Travelling Salesman Problem
Keywords:
Genetic Algorithm, Travelling Salesman Problem, Initial Population, Mutation, Crossover.Abstract
In this paper, software was developed to solve the travelling salesman problem. The Travelling Salesman Problem is a computational optimization problem that requires a lot of time to solve using brute force algorithm. The research aims at developing java-based software that provides an optimum solution to the Travelling Salesman Problem using the concepts of genetic algorithm within reasonable time frame.
References
. Jean-Yves, P. (1996) ‘Genetic algorithms for the travelling salesman problem’, Annals of Operations Research. 63(3), pp 337-370
. Dario, F. and Claudio M. (2008) Bio-Inspired Artificial Intelligence. London: The MIT Press Cambridge, Massachusetts.
. Holland, J. H., Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI, USA,1975.
. ‘Genetic Algorithm’ (2014) Wikipedia. Available at: http://en.wikipedia.org/wiki/Genetic_algorithm (accessed on 24/06/2014)
. Sivanandan, S.N., and Deepa, S.N. (2008) Introduction to Genetic Algorithms, Springer
. Pedro A. and Dean F. (2007) Initial Population for Genetic Algorithm: A metric Approach: School of computer science, University of Oklahoma, Norman. USA. Available at: http://www.cameron.edu/~pdiaz-go/GAsPopMetric.pdf (accessed 12/08/2014)
. Uniform crossover (2014) Wikipedia. Available at: http://en.wikipedia.org/wiki/Crossover_(genetic_algorithm) (accessed on 26/06/2014)
. Proportionate Selection (2014) Wikipedia. Available at: http://en.wikipedia.org/wiki/Fitness_proportionate_selection(accessed on 27/06/2014)
. Khalid J., and Mohammed M.,(2013) ‘Selection Methods for Genetic Algorithms’ int. J. Emerg. Sci. 3(4), pp.333-334. Available at: http://ijes.info/3/4/42543401.pdf
. Goldberg E., and Lingle R., ‘Alleles, loci, and travelling salesman problem’. InProc. Of the International Conference on Genetic Algorithms and Their Applications, pp. 154-159, Pittsburgh, PA, 1985.
. Oliver, I.M., and Smith, D.J., and Holland, J.R.C. ‘A study of permutation crossover operation on travelling salesman problem’. Proceedings of the second International Conference on Genetic Algorithms on Genetic algorithm and their application, pp. 244-230. NJ, USA 1987.
. Noraini M., and John G., (2011) ‘Genetic Algorithm performance with Different Selection Strategies in Solving TSP’, Proceedings of the World Congress on Engineering. Vol II, London, U.K. Available at: http://www.iaeng.org/publication/WCE2011/WCE2011_pp1134-1139.pdf (accessed 28/06/2014)
. Lee (2012) Applying a genetic algorithm to the traveling salesman problem http://www.theprojectspot.com/tutorial-post/applying-a-genetic-algorithm-to-the-travelling-salesman-problem/5 (accessed 28/06/2014)
. Goldberg, D. E., Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, New York, NY, 1989.
. Zbigniew, M., (1994) Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, 2nd edition, 1994.
. Rajesh, M., Surya, P. S., and Murari, L. M., (2010) Travelling Salesman Problem :An Overview of Applications, Formulations, and Solution Approaches; Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, Available at: http://cdn.intechopen.com/pdfs-wm/12736.pdf (accessed 12/08/2014)
. Zhifeng, H., Huang, H., and Cai, R., (2008) Bio-inspired Algorithms for TSP and Generalized TSP. Travelling Salesman Problem. Shanghai, China. Available at: http://cdn.intechweb.org/pdfs/4606.pdf (accessed 20/08/2014)
. Kumar R., Gopal G., (2013) ‘Novel Crossover Operator for Genetic Algorithm for Permutation Problems’, International Journal of Soft Computing and Engineering 3(2) pp. 2231-2307
. MATLAB www.matlab.com
. Heaton, J., 2005. Introduction to Neutral Network with Java. (1st ed). U.S.A: Heaton Research, Inc.
. Deitel, P. and Deitel, H., (2013) Java: How to Program. (9th ed). New Jersey, U.S.A: Pearson Education, Inc.
. Cornell and Horstmann (2008) Core Java, volume I/II (8th ed). U.S,A :Prentice Hall
. Lewis, J. and Loftus, W., (2007). Java Software Solution: foundations of program design. (5th ed). U.S.A: Addison Wesley
. Noraini, M and John G., (2011) ‘Genetic Algorithm Performance with Different Selection Strategies in solving TSP’. Proceedings of the World Congress on Engineering Vol II, London, U.K
. Srinivas, M., and Patnaik, L.M., (1994) ‘Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms’. IEEE Transactions on System, man and cybernetic, Vol. 24, No 4, April 1994.
Downloads
Published
How to Cite
Issue
Section
License
Authors who submit papers with this journal agree to the following terms.
