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Shortest Path Calculation Using Swarm Techniques for Communication among Agents in a Network


Affiliations
1 Department of Computer Application, Shri Ramswaroop Memorial University, Lucknow Deva Road, Uttar Pradesh, India
     

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Identifying the shortest route between two nodes is a well-known problem in computing world. As there are lot of subsequent growth in computational power in last few years which has provided independent to implement intensive intelligent algorithms. Various proven traditional static algorithms, such as Diskastra’s algorithm, kruskal’s algorithm and Prim’s algorithm are extensively evaluated and implemented. In this paper there is use of Swarm Intelligence Algorithm which is various in natures i.e. Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Artificial Bee Colony (ABC). Study represented in this paper is responsible to apply article swarm optimization with various parameters to optimize the time and cost. 

Keywords

Intelligence, Optimization, Shortest Path, Filtering.
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  • Abdelkafi, O., Idoumghar, L., Lepagnot, J.: Comparison of two diversification methods to solve the quadratic assignment problem. Procedia Comput. Sci. 51, 2703–2707 (2015)

  • Abdelsadek, Y., Chelghoum, K., Herrmann, F., Kacem, I., Otjacques, B.: Community detection algorithm based on weighted maximum triangle packing. In: Proceedings of International Conference on Computer and Industrial Engineering CIE45 (2015).

  • Abdelsadek, Y., Chelghoum, K., Herrmann, F., Kacem, I., Otjacques, B.: Visual interactive approach for mining twitter’s networks. In: Tan, Y., Shi, Y. (eds.) Data Mining and Big Data. LNCS, vol. 9714, pp. 342–349. Springer, Heidelberg (2016)

  • Alvari, H., Hajibagheri, A., Sukthankar, G.R.: Community detection in dynamic social networks: A game-theoretic approach. In: Wu, X., Ester, M., Xu, G. (eds.) ASONAM, pp. 101–107. IEEE Computer Society (2014)

  • Bansal, S., Bhowmick, S., Paymal, P.: Fast community detection for dynamic complex networks. In: F. Costa, L., Evsukoff, A., Mangioni, G., Menezes, R. (eds.) CompleNet 2010. CCIS, vol. 116, pp. 196–207. Springer, Heidelberg (2011).

  • Beroule, B., Grunder, O., Barakat, O., Aujoulat, O., Lustig, H.: Ordonnancement des interventions chirurgicales d’un hopital avec prise en compte de l’étape de stérilisation dans un contexte multi-sites (2016)

  • Blondel, V., Guillaume, J., Lambiotte, R., Mech, E.: Fast unfolding of communities in large networks. J. Stat. Mech. 10, 10008 (2008)

  • Bonabeau, E., Dorigo, M., Theraulaz, G.: Inspiration for Optimization from Social Insect Behavior. Nature 406, 39–42 (2002)

  • Clerc, M., Kennedy, J.: The Particle Swarm: Explosion, Stability, and Convergence in a Multi-dimensional Complex Space. IEEE Transactions on Evolutionary Computation 6,58–73 (2002)

  • Czapinski, M.: An effective parallel multistart tabu search for quadratic assignment problem on CUDA platform. J. Parallel Distrib. Comput. 73, 1461–1468 (2013).

  • Czapinski, M.: An effective parallel multistart tabu search for quadratic assignment problem on CUDA platform. J. Parallel Distrib. Comput. 73, 1461–1468 (2013)

  • Debasmita Mukherjee,Ant Colony Optimization Technique Applied in Network Routing Problem ”, International Journal of Computer Applications.

  • Dokeroglu, T.: Hybrid teaching-learning-based optimization algorithms for the quadratic assignment problem. Comput. Ind. Eng. 85, 86–101 (2015).

  • Grosan, C., Abraham, A., Monica, C.: Swarm Intelligence in Data Mining. In: Abraham,A., Grosan, C., Ramos, V. (eds.) Ant Colony Optimization Intelligence in Data Mining. SCI, vol. 34, pp. 1–16. Springer, Heidelberg (2006).

  • Mendes, R., Kennedy, J., Neves, J.: The Fully Informed Particle Swarm: Simpler, may be Better. IEEE Transactions on Evolutionary Computation 8, 204–210 (2004)

  • Rutger Claes DistriNet Labs, Ant Colony Optimization applied to Route Planning using Link Travel Time predictions, IEEE International Parallel & Distributed Processing Symposium, (2011).

  • Rutger Claes DistriNet Labs, Solving Traveling Salesman Problem by Using Improved Ant Colony Optimization Algorithm”, International Journal of Information and Education Technology, Vol. 1, No. 5, December (2011).

  • S.Aravindh and Mr.G.Michael,Hybrid of ant colony optimization and genetic algorithm for shortest path in wireless mesh networks, Volume 3, No. 1, January 2012 Journal of Global Research in Computer Science.

  • Seeley, T.D.: The Wisdom of the Hive. Harward University Press (1996) z

  • Subbotina, S.A., Oleinik, A.A.: Multiagent Optimizaiton based on the Bee-Colony Method. Cybernetics and Systems Analysis 45, 177–186 (2009)

  • Tosun, U.: On the performance of parallel hybrid algorithms for the solution of the quadratic assignment problem. Eng. Appl. Artif. Intell. 39, 267–278 (2015).

  • Vikas Singh, Deepak Singh, ”Path Planning Using Particle Swarm Optimization with Linear Crossover Operator, Advances in Mathematical and Computational Methods, ISSN 2160-0635 Volume 2, Number 1, March, (2012).

  • Yang, X.S.: Engineering Optimizations via Nature-Inspired Virtual Bee Algorithms. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3562, pp. 317–323. Springer, Heidelberg (2005)

  • Yizhen Huang, Qingming Yi, Min Shi , {An Improved Dijkstra’s Shortest Path Algorithm},Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering- ICCSEE (2013)


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  • Shortest Path Calculation Using Swarm Techniques for Communication among Agents in a Network

Abstract Views: 261  |  PDF Views: 3

Authors

Abhishek Sachan
Department of Computer Application, Shri Ramswaroop Memorial University, Lucknow Deva Road, Uttar Pradesh, India
Bineet Kumar Gupta
Department of Computer Application, Shri Ramswaroop Memorial University, Lucknow Deva Road, Uttar Pradesh, India

Abstract


Identifying the shortest route between two nodes is a well-known problem in computing world. As there are lot of subsequent growth in computational power in last few years which has provided independent to implement intensive intelligent algorithms. Various proven traditional static algorithms, such as Diskastra’s algorithm, kruskal’s algorithm and Prim’s algorithm are extensively evaluated and implemented. In this paper there is use of Swarm Intelligence Algorithm which is various in natures i.e. Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Artificial Bee Colony (ABC). Study represented in this paper is responsible to apply article swarm optimization with various parameters to optimize the time and cost. 

Keywords


Intelligence, Optimization, Shortest Path, Filtering.

References