Using Genetic Algorithm with Combinational Crossover to Solve Travelling Salesman Problem
Ammar Al-Dallal
2015
Abstract
This paper proposes a new solution for Traveling Salesman Problem (TSP) using genetic algorithm. A combinational crossover technique is employed in the search for optimal or near-optimal TSP solutions. It is based upon chromosomes that utilise the concept of heritable building blocks. Moreover, generation of a single offspring, rather than two, per pair of parents, allows the system to generate high performance chromosomes. This solution is compared with the well performing Ordered Crossover (OX). Experimental results demonstrate that, due to the well structured crossover technique, has enhanced performance.
References
- Yuan L., Lu Y., Li M., 2009. "Genetic Algorithm Based on Good Character Breed for Traveling Salesman Problem," 1st International Conference Information Science and Engineering (ICISE), pp.234,237, 26-28 Dec.
- Vahdati, G., Yaghoubi, M., Poostchi, M., Naghibi S, M.B., 2009. "A New Approach to Solve Traveling Salesman Problem Using Genetic Algorithm Based on Heuristic Crossover and Mutation Operator," International Conference of Soft Computing and Pattern Recognition. SOCPAR 7809, pp.112,116, 4-7 Dec.
- Wang S., Zhao A., 2009. "An Improved Hybrid Genetic Algorithm for Traveling Salesman Problem", International Conference on Computational Intelligence and Software Engineering,. CiSE 2009. , vol., no., pp.1,3, 11-13 Dec.
- Zhao G., Luo W., Nie H., Li C., 2008. "A Genetic Algorithm Balancing Exploration and Exploitation for the Travelling Salesman Problem," Fourth International Conference on Natural Computation, ICNC 7808. , vol.1, pp.505,509, 18-20 Oct.
- Yu Y., Chen Y., Li T., 2011. "A New Design of Genetic Algorithm for Solving TSP," Fourth International Joint Conference on Computational Sciences and Optimization (CSO), pp.309- 313, 15-19 April.
- Lianshuan S., Zengyan L., 2009. "An Improved Pareto Genetic Algorithm for Multi-objective TSP," Fifth International Conference on Natural Computation, ICNC 7809 , vol.4, pp.585,588, 14-16 Aug.
- Takahashi, R., 2011. "Solving the Traveling Salesman Problem through Iterative Extended Changing Crossover Operators," 10th International Conference on Machine Learning and Applications and Workshops (ICMLA), 2011, vol.1, pp.253,258, 18-21 Dec.
- Kuroda, M., Yamamori, K., Munetomo, M., Yasunaga, M., Yoshihara, I., 2010. "A proposal for Zoning Crossover of Hybrid Genetic Algorithms for largescale traveling salesman problems," IEEE Congress on Evolutionary Computation (CEC), , vol., no., pp.1,6, 18-23 July.
- Razali M.. R., and Geraghty J., 2011. "Genetic algorithm performance with different selection strategies in solving TSP”, World Congress Engineering 2011, vol II WCE,(London UK).
- Sallabi O., El-Haddad Y.. 2009. An Improved Genetic Algorithm to Solve the Travelling Salesman Problem. World Academy of Science, Engineering and Technology. vol.52, pp. 471-474.
- Otman A., Abouchabaka J., 2012. "A comparative study of adaptive crossover operators for genetic algorithms to resolve the traveling salesman problem." IJCA, vol.31, no. 11, pp. 49-57.
- Osaba E., Onieva E., Carballedo R., Diaz F., Perallos A., and Zhang X., 2013. “A multi-crossover and adaptive island based population algorithm for solving routing problems,” Journal of Zhejiang University SCIENCE C, vol. 14, no. 11, pp. 815-821.
- Aly A., 1990. “Applying genetic algorithm in query improvement problem”. Information Technologies and Knowledge, vol.1, pp. 309-316.
- Yeh, J.-Y., Lin, J.-Y., Ke, H.-R., and Yang, W.-P., 2007. “Learning to rank for information retrieval using genetic programming”. In Proceedings of ACM SIGIR Workshop on Learning to Rank for Information Retrieval (LR4IR 7807), pp. 41-48. Amsterdam, Netherlands.
- Asllani, A., Lari, A., 2007. “Using genetic algorithm for dynamic and multiple criteria web-site optimization”s, European Journal of Operational Research, Volume 176, Issue 3, 1 February 2007, pp. 1767-1777.
- Vrajitoru D., 1998. “Crossover improvement for the genetic algorithm in information retrieval”. Information Processing and Management , vol. 34, no. 4, ,pp. 405-415.
- Reinelt G., 1991. “TSPLIB - a traveling salesman problem library”, ORSA Journal on Computing, , Vol.3, No.4, pp.376-384.
Paper Citation
in Harvard Style
Al-Dallal A. (2015). Using Genetic Algorithm with Combinational Crossover to Solve Travelling Salesman Problem . In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 149-156. DOI: 10.5220/0005590201490156
in Bibtex Style
@conference{ecta15,
author={Ammar Al-Dallal},
title={Using Genetic Algorithm with Combinational Crossover to Solve Travelling Salesman Problem},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={149-156},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005590201490156},
isbn={978-989-758-157-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - Using Genetic Algorithm with Combinational Crossover to Solve Travelling Salesman Problem
SN - 978-989-758-157-1
AU - Al-Dallal A.
PY - 2015
SP - 149
EP - 156
DO - 10.5220/0005590201490156