¹School of Automation, Guangdong University of Technology, Guangzhou, China; School of Mathematics & Computer Science, GanNan Normal University, Ganzhou, China
²School of Computers, Guangdong University of Technology, Guangzhou, China; School of Electronic Engineering, Dongguan University of Technology, Dongguan, China; Intelligent Autonomous Systems Lab, University of the West of England, Bristol, UK

---

Abstract—In this paper the torsion bar optimization problem of reliability is considered. Since this problem is a difficult optimization problem, an improved intelligent ant colony algorithm is proposed to solve the problem. This algorithm comprises five stages. First stage is the initialization of pheromone and the sensor node configuration. The second stage is to select the next sensor node. The third stage is to update the pheromone of the sensor node path. The fourth stage is to acquire the best path by computing the shortest distance. The last stage is to output the global optimal solution. To evaluate performance of the proposed algorithm, it is compared with the ant colony optimization algorithm and the genetic algorithm. The experimental results show that the proposed algorithm performs better than them.

Index Terms—Intelligence algorithm, CPS, Optimization, Reliability, Manufacturing

[PDF]

Cite: Shiliang Luo, Lianglun Cheng, Bin Ren, and Quanmin Zhu, "An Improved Intelligent Ant Colony Algorithm for the Reliability Optimization Problem in Cyber-Physical Systems," Journal of Software vol. 9, no. 1, pp. 20-25, 2014.