Advertisement

Chemical Reaction Optimization for Traveling Salesman Problem Over a Hypercube Interconnection Network

  • Ameen Shaheen
  • Azzam Sleit
  • Saleh Al-Sharaeh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 765)

Abstract

Traveling Salesman Problem is a well-known NP-Hard problem, which aims at finding the shortest path between numbers of cities. Chemical Reaction Optimization (CRO) is a recently established meta-heuristic algorithm for solving optimization problems which has successfully solved many optimization problems. The main goal of this paper is to investigate the possibility of parallelizing CRO for solving the TSP problem called (PCRO). PCRO is compared with Genetic Algorithm (GA), which is a well-known meta-heuristic algorithm. Experimental results show relatively better performance for PCRO in terms of execution time, Speedup, optimal cost and Error rate.

Keywords

Chemical reaction optimization Meta-heuristics Traveling salesman problem 

References

  1. 1.
    Vukmirović, S., Pupavac, D.: The Travelling Salesman Problem in the Function of Transport Network Optimalization. Fakulty of Economics, Interdisciplinary Management Research IX, University in Osijek, Osijek (2013)Google Scholar
  2. 2.
    Zhan, F., Noon, C.: Shortest path algorithms: an evaluation using real road networks. Transp. Sci. (1996)Google Scholar
  3. 3.
    Al-Shaikh, A., Khattab, H., Sharieh, A., Sleit, A.: Resource utilization in cloud computing as an optimization problem. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 7(6), 336–342 (2016)Google Scholar
  4. 4.
    Hoffman, K.L., Padberg, M., Rinaldi, G.: Traveling salesman problem. In: Encyclopedia of Operations Research and Management Science, pp 1573–1578. Springer (2016)CrossRefGoogle Scholar
  5. 5.
    Lam, A.Y.S., Li, V.O.K.: Chemical reaction optimization: a tutorial. Memet. Comput. 4, 3–17 (2012)CrossRefGoogle Scholar
  6. 6.
    Barney, B.: Introduction to Parallel Computing. Lawrence Livermore National Laboratory (2007). https://computing.llnl.gov/tutorials/parallel_comp/
  7. 7.
    Sleit, A., Salah, I., Jabay, R.: Approximating images using minimum bounding rectangles. In: ICADIWT 2008, pp. 394–396 (2008)  https://doi.org/10.1109/ICADIWT.2008.4664379
  8. 8.
    Ostrouchov, G.: Parallel computing on a hypercube: an overview of the architecture and some applications. In: Heiberger, R.M. (ed.) Proceedings of the 19th Symposium on the Interface of Computer Science and Statistics, pp. 27–32. American Statistical Association (1987)Google Scholar
  9. 9.
    Kiasari, A., Sarbazi-Azad, H.: Analytic performance comparison of hypercubes and star graphs with implementation constraints. J. Comput. Syst. Sci. 74(6), 1000–1012 (2008)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Cathleen, L.: “Inside a NASA Production Supercomputing Center” Concept To Reality magazines, Summer/Fall issue (2011)Google Scholar
  11. 11.
    Mohan, A., Remya, G.: A parallel implementation of ant colony optimization for TSP based on MapReduce framework. Int. J. Comput. Appl. 88(8), 9–12 (2014)Google Scholar
  12. 12.
    Er, H.R., Erdogan, N.: Parallel genetic algorithm to solve traveling salesman problem on MapReduce framework using Hadoop cluster”. arXiv preprint arXiv:1401.6267 (2014)
  13. 13.
    Sun, J., Wang, Y., Li, J., Gao, K.: Hybrid algorithm based on chemical reaction optimization and Lin-Kernighan local search for the traveling salesman problem (2011)Google Scholar
  14. 14.
    Shaheen, A., Sleit, A.: Comparing between different approaches to solve the 0/1 Knapsack problem. Int. J. Comput. Sci. Netw. Secur. 16(7), 1–10 (2016)Google Scholar
  15. 15.
    Barham, R., Sharieh, A., Sliet, A.: Chemical reaction optimization for max flow problem. (IJACSA) Int. J. Adv. Comput. Sci. Appl. 7(8), 189–196 (2016)Google Scholar
  16. 16.
    Deb, K.: An introduction to genetic algorithms. Sadhana 24(4–5), 293–315 (1999)MathSciNetCrossRefGoogle Scholar
  17. 17.
    TSP Website: A collection of worldwide benchmark datasets (2009). http://www.math.uwaterloo.ca/tsp/world/countries.html. Accessed 15 Dec 2017

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Computer Science Department, King Abdullah II School for Information TechnologyThe University of JordanAmmanJordan

Personalised recommendations