An Improved African Buffalo Optimization Algorithm for Collaborative Team Formation in Social Network

Full Text (PDF, 934KB), PP.16-29

Views: 0 Downloads: 0

Author(s)

Walaa H. El-Ashmawi 1,*

1. Computer Science Department, Faculty of Computers and Informatics, Suez Canal University, Ismailia, 41522, Egypt

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2018.05.02

Received: 20 Jan. 2018 / Revised: 22 Feb. 2018 / Accepted: 20 Mar. 2018 / Published: 8 May 2018

Index Terms

African Buffalo Optimization, Team Formation, Social Network, Swap Sequence, Discrete crossover

Abstract

Collaborative team formation in a social network is an important aspect for solving a real-world problem that requires different expert skills to achieve it. In this paper, we propose an improved African Buffalo Optimization algorithm integrated with discrete crossover operator conjointly with swap sequence for efficient team formation whose members can assist in solving a given problem with minimum communication cost. The proposed algorithm is called Improved African Buffalo Optimization algorithm (IABO).  In IABO, a new concept of swap sequence applied to improve the performance by generating better team members that cover all the required skills. To the best of our knowledge, this is the first work that considers the African Buffalo Optimization algorithm for collaborative team formation in a social network of experts. A set of experiments have been done on two popular real-world benchmark datasets (i.e., DBLP and Stack Overflow) to determine the efficiency of the proposed algorithm in team formation. The results demonstrate the effectiveness of the IABO algorithm in comparison with GA, PSO and standard African Buffalo Optimization algorithm (ABO).

Cite This Paper

Walaa H. El-Ashmawi, "An Improved African Buffalo Optimization Algorithm for Collaborative Team Formation in Social Network", International Journal of Information Technology and Computer Science(IJITCS), Vol.10, No.5, pp.16-29, 2018. DOI:10.5815/ijitcs.2018.05.02

Reference

[1]T. Lappas, K. Liu, E. Terzi. “Finding a team of experts in social networks”. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and datamining. 2009, pp. 467-47.

[2]E.G. Talbi. “Metaheuristics: from design to implementation”. Wiley, 2009, Vol. (74).

[3]Theodoros Lappas, Kun Liu, Evimaria Terzi.  “A survey of algorithms and systems for expert location in social networks”. Social network data analytics, Springer, 2011, pp. 215–241.

[4]Sangita Roy, Samir Biswas, Sheli Sinha Chaudhuri, “Nature-Inspired Swarm Intelligence and Its Applications”. IJMECS, vol.6, no.12, pp.55-65, 2014.DOI: 10.5815/ijmecs.2014.12.08.

[5]J. B Odili, M. N. M. Kahar. “African Buffalo Optimization (ABO): a New Meta-Heuristic Algorithm”. Journal of Advanced & Applied Sciences, April 2015, Vol. (03): 101-106.

[6]J. B Odili, M. N. M. Kahar. “Numerical Function Optimization Solutions Using the African Buffalo Optimization Algorithm (ABO)”.  British Journal of Mathematics & Computer Science, 2015,10(1): 1-12.

[7]J. B Odili, M. N. M. Kahar, A. Noraziah. “Convergence Analysis of the African Buffalo Optimization Algorithm”. In International Journal of Simulation: Systems, Science & Technology (IJSSST), April 2017, 17(33).

[8]J. B Odili, M. N. M. Kahar. “Solving the Traveling Salesman’s Problem Using the African Buffalo Optimization”. Computational Intelligence and Neuroscience, Hindawi Publishing Corporation, 2016.

[9]J. B Odili, M. N. M. Kahar, S. Anwar, M. Ali. “Tutorials on African Buffalo Optimization for Solving the Traveling Salesman Problem”.  In International Journal of Software Engineering and Computer Systems (IJSECS), February 2017, Vol.(3):120-128.

[10]J. B Odili, M. N. M. Kahar,  A. Noraziah,  E. A.  Odili. “African Buffalo optimization and the randomized insertion algorithm for the asymmetric travelling salesman’s problems”. Journal of Theoretical and Applied Information Technology, May 2016,Vol.87(3).

[11]A. Anagnostopoulos, L. Becchetti, C. Castillo, A. Gionis, , S. Leonardi. “Online team formation in social networks”. In Proceedings of the 21st international conference on World Wide Web, ACM, 2012, pp. 839–848.

[12]A. Gajewar, , A.D. Sarma. “Multi-skill collaborative teams based on densest subgraphs”. In SDM, 2012, pp. 165–176.

[13]M. Kargar, M. Zihayat,  A. An. “Finding affordable and collaborative teams from a network of experts”. In Proceedings of the 2013 SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, 2013, pp. 587-595.

[14]M. Kargar,  A. An, “Discovering top-k teams of experts with/without a leader in social Networks”.  In Proceedings of the 20th ACM international conference on Information and knowledge management, 2011, pp. 985-994.

[15]Ana Paula Appel, Victor F. Cavalcante, Marcos R. Vieira,. Vagner F. de Santana, RA de Paula, Steven K Tsukamoto. “Building socially connected skilled teams to accomplish complex tasks,” In Proceedings of the 8th Workshop on Social Network Mining and Analysis, 2014.

[16]Li, CT., Shan, MK. “Team formation for generalized tasks in expertise social networks,” IEEE Second International Conference on Social Computing (SocialCom), pp. 9-16, 2010.

[17]CT. Li, MK. Shan, SD. Lin. “On team formation with expertise query in collaborative social networks”. Knowledge and Information Systems, 2015,42(2): 441-463.

[18]Aris Anagnostopoulos , Luca Becchetti, Carlos Castillo, Aristides Gionis, Stefano Leonardi. “Power in unity: forming teams in large-scale community systems”. In Proceedings of the 19th ACM international conference on Information and knowledge management, 2010, pp. 599-608.

[19]J. Huang, X. Sun, Y. Zhou, H. Sun. “A Team Formation Model with Personnel Work Hours and Project Workload Quantified” .The Computer Journal, 2017, pp. 1-13.

[20]RL. Haupt, SE. Haupt. “Practical genetic algorithms,” John Wiley & Sons, 2004.

[21]C. Blum, A. Roli. “Metaheuristics in combinatorial optimization: Overview and conceptual comparison”. ACM Computing Surveys (CSUR), 2003, 35(3): 268-308.

[22]K. Pashaei, F. Taghiyareh,  K. Badie. “A recursive genetic framework for evolutionary decision-making in problems with high dynamism”.  International Journal of Systems Science, 2015, 46(15): 2715-2731.

[23]D. Sedighizadeh, E. Masehian. “Particle swarm optimization methods, taxonomy and Applications”. International Journal of Computer Theory and Engineering, 2009, 1(5): 486-502.

[24]Hamza O. Salami, Esther Y. Mamman, “A Genetic Algorithm for Allocating Project Supervisors to Students”. International Journal of Intelligent Systems and Applications (IJISA), Vol.8, No.10, pp.51-59, 2016. DOI: 10.5815/ijisa.2016.10.06

[25]JW. Zhang, WJ. Si. “Improved enhanced self-tentative PSO algorithm for TSP”.  In Sixth International Conference on Natural Computation (ICNC), 2010, Vol. (5):2638-2641.

[26]M. Nadershahi, RT. Moghaddam. “An application of genetic algorithm methods for team formation on the basis of Belbin team role”. Archives of Applied Science Research,  2012, 4(6): 2488-2496.

[27]Mohammad Fathian, Mohamad Saei-Shahi , Ahmad Makui. “A New Optimization Model for Reliable Team Formation Problem Considering Experts Collaboration Network”.  IEEE Transactions on Engineering Management, 2017.

[28]T. G. Dominik. “Genetic Algorithms Reference”.  Volume –I, Poland: Tomasz Gwiazda, 2006.

[29]KP. Wang, L. Huang, CG. Zhou, W. Pang. “Particle swarm optimization for traveling  salesman problem”. In International Conference on Machine Learning and Cybernetics, 2003, Vol. (3): 1583-1585.

[30]X. Wei, Z. Jiang-wei, Z. Hon-lin. “Enhanced Self-Tentative Particle Swarm Optimization Algorithm for TSP”. Journal of north china electric power university, 2009, 36(6): 69-74.

[31]JW. Zhang,  WJ. Si. “Improved enhanced self-tentative PSO algorithm for TSP”. In Sixth International Conference on Natural Computation (ICNC) , 2010, Vol. (5):2638-2641.

[32]M. A. H. Akhand, Pintu Chnadra Shill, Md. Forhad Hossain, A. B. M. Junaed, K. Murase, “Producer-Scrounger Method to Solve Traveling Salesman Problem”. International Journal of Intelligent Systems and Applications (IJISA), vol.7, no.3, pp.29-36, 2015. DOI:10.5815/ijisa.2015.03.04.

[33]M. Mitchell. An Introduction to Genetic Algorithms. Cambridge, MA: MIT Press (1996).

[34]RC. Eberhart, Y. Shi, J. Kennedy. “Swarm Intelligence”. The Morgan Kaufmann Series in Evolutionary Computation, 2001.