Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Xie, Yongquan; Zhou, Zude; Pham, Duc Truong; Xu, Wenjun; Ji, Chunqian (2015)
Publisher: Hindawi Publishing Corporation
Journal: Computational Intelligence and Neuroscience
Languages: English
Types: Article
Subjects: R858-859.7, Computer applications to medicine. Medical informatics, Research Article, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, QA76, Article Subject
In order to realize an optimal resource service allocation in current open and service-oriented manufacturing model, multiuser resource service composition (RSC) is modeled as a combinational and constrained multiobjective problem. The model takes into account both subjective and objective quality of service (QoS) properties as representatives to evaluate a solution. The QoS properties aggregation and evaluation techniques are based on existing researches. The basic Bees Algorithm is tailored for finding a near optimal solution to the model, since the basic version is only proposed to find a desired solution in continuous domain and thus not suitable for solving the problem modeled in our study. Particular rules are designed for handling the constraints and finding Pareto optimality. In addition, the established model introduces a trusted service set to each user so that the algorithm could start by searching in the neighbor of more reliable service chains (known as seeds) than those randomly generated. The advantages of these techniques are validated by experiments in terms of success rate, searching speed, ability of avoiding ingenuity, and so forth. The results demonstrate the effectiveness of the proposed method in handling multiuser RSC problems.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • ( 60 d
    • n 40 ie
    • s 20 d
    • F 0 100 90 )(%80 e tra70 s sce60 c Su50 40 30 80
    • v 40 icen
    • s 20 adu
    • F 0 100 90
    • ( 60 d
    • n 40 ie
    • s 20 d
    • F 0 80
    • v 40 i
    • s 20 d
    • F 0 20
    • Proceedings of the 5th Virtual International Conference on Inno-
    • vative Production Machines and Syste,mpsp. 05- 10, Cardif,
    • UK, 2009. [25] D. Pham, A. H. Darwish, and E. Eldukhri, “Optimisation of a
    • Journal of Computer Aided Engineering and Technolog, yvol. 1,
    • no. 2, pp. 250-26 , 2009. [26] D. T. Pham and E. K¸o, c“Design of a two-dimensional recur-
    • Automation and Computin, gvol. 7, no. 3, pp. 399- 02, 2010. [27] D. T. Pham and A. Haj Darwish, “Using the bees algorithm with
    • 22 , no. 7, pp. 885-892, 2010. [28] M. Castellani, Q. T. Pham, and D. T. Pham, “Dynamic optimisa-
    • Engineering, vol. 226, no. 7, pp. 956-971, 2012.
  • No related research data.
  • No similar publications.