A Multiuser Manufacturing Resource Service Composition Method Based on the Bees Algorithm.
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.
School of Information Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan 430070, China ; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China ; School of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B152TT, UK.
Yongquan
Y
Xie
School of Information Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan 430070, China ; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China.
Zude
Z
Zhou
School of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B152TT, UK.
Duc Truong
DT
Pham
School of Information Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan 430070, China ; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China.
Wenjun
W
Xu
School of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B152TT, UK.
Chunqian
C
Ji
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003199:Computer Systems; D008962:Models, Theoretical