Optimization of Resource Service Composition in Cloud Manufacture Based on Improved Genetic and Ant Colony Algorithm

Abstract

Aiming at resource service composition optimization under cloud manufacturing, a service composition and optimization objective function model for cloud manufacturing resource based on quality of service was established. An improved genetic and ant colony algorithm to solve the model was also proposed. The hybrid algorithm combined the advantages of local optimization of ant colony algorithm and global search of genetic algorithm. The improved algorithm can solve slow convergence speed and easy to fall into local optimum existed in ant colony algorithm, also can solve local search ability poor and easy to premature convergence existed genetic algorithm. Simulation results showed that the algorithm contributed to reducing problem search space and time, and can achieve identifying and matching of resource services quickly and accurately. The improved algorithm can solve the optimization problem of cloud manufacturing resource services composition more effectively.

Tasks

Reproductions