Data Research, Vol. 2, Issue 1, Feb  2018, Pages 18-32; DOI: 10.31058/j.data.2018.21002 10.31058/j.data.2018.21002

Research on the Internet of Things Based on Ant Colony Optimization Algorithm

, Vol. 2, Issue 1, Feb  2018, Pages 18-32.

DOI: 10.31058/j.data.2018.21002

Yibin Hou 1* , Jin Wang 1

1 School of Software Engineering, Department of Information, Beijing University of Technology, Beijing, China

Received: 1 December 2017; Accepted: 25 December 2017; Published: 8 February 2018

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Abstract

The purpose of this paper is to prove that the ant colony algorithm is an excellent mathematical modeling method and improve the production efficiency of the single drilling machine. The methods of mathematical induction and mathematical deduction and mathematical hypothesis are commonly used mathematical methods in scientific research. The ant colony algorithm to solve the TSP problem: algorithm design ideas: using the standard ant colony algorithm or its improved to achieve a traveling salesman problem TSP, find the shortest distance of the 51 City, the number of iterations is 1000 times, the final output of the optimal solution. Algorithm flow: (1) initialize ant colony: initialize ant colony parameter, set ant number, ant put in 51 vertices, initialize path pheromone. (2) Ant action: the ants leave their paths by the ants in front of the pheromone and their own judgments to complete a loop path. (3) Releasing pheromones: the path to releasing ants through a certain percentage of pheromones. (4) The evaluation of ants: the fitness is evaluated according to the objective function of each ant. (5) If the shortest path condition is satisfied, the optimal output is obtained. Otherwise, the algorithm continues. (6) Pheromones evaporate: pheromones continue to dissipate over time. The result of this paper is that the ant colony algorithm has high accuracy and efficiency; the TSP problem can be solved, to improve the production efficiency of the single drilling machine. The conclusion of this paper is that ant colony algorithm is an excellent algorithm, the TSP problem can be solved, for example, can improve the production efficiency of the single drilling machine.

Keywords

Internet of Things, Colony Optimization Algorithm, TSP Problem, the Production Efficiency of the Single Drilling Machine

Copyright

© 2017 by the authors. Licensee International Technology and Science Press Limited. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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