Complex Vehicle Scheduling Optimization Problem Based on Improved Ant Colony Algorithm

2012 ◽  
pp. 805-812 ◽  
Author(s):  
Yong Zeng ◽  
Dacheng Liu ◽  
Xiangyu Hou
Keyword(s):  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Vehicle Scheduling ◽  
Scheduling Optimization ◽  
Improved Ant Colony Algorithm

Improved Ant Colony Algorithm on Scheduling Optimization of Cloud Computing Resources

2014 ◽  
Vol 678 ◽  
pp. 75-78
Author(s):  
Xiao Xi Hu ◽  
Xian Wei Zhou
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Ant Colony Algorithm ◽  
Response Speed ◽  
Ant Colony ◽  
Prediction Algorithm ◽  
Trend Prediction ◽  
Scheduling Optimization ◽  
Scheduling Optimization Algorithm ◽  
Improved Ant Colony Algorithm

To address the problem of high occupancy of resources and slow response of current scheduling of cloud computing resources, this paper proposes a scheduling optimization algorithm based improved ant colony algorithm. It makes resource reservation through migration of virtual machine, uses dynamic trend prediction algorithm to forecast the load changes of data center, and puts forward the concrete complement to adjust reduction. Experiments show that the combination algorithm proposed in this paper are efficient to improve the performance of data center, accelerate the response speed and increase the precision.

An Improved Ant Colony Algorithm Based on Path Optimization Strategy for TSP

2014 ◽  
Vol 543-547 ◽  
pp. 1681-1684 ◽  
Author(s):  
Ben Can Gong ◽  
Ting Yao Jiang ◽  
Shou Zhi Xu ◽  
Peng Chen
Keyword(s):  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Optimal Solution ◽  
Ant Colony ◽  
Path Optimization ◽  
Optimization Strategy ◽  
Local Optimal Solution ◽  
Np Hard Problem ◽  
Improved Ant Colony Algorithm ◽  
High Application

Traveling salesman problem (TSP) is not only a combinatorial optimization problem but also a classical NP-hard problem, which has high application value. Ant colony algorithm (ACA) is very effective for solving TSP problem, but basic ant colony algorithm has drawbacks of low convergence rate and easily trapping in local optimal solution. An improved ant colony algorithm was proposed. It used path optimization strategy to exchange the position of cities to find the better solution for TSP. Simulation results show the improved algorithm has better optimal solution and higher efficiency.

Sign in / Sign up

Export Citation Format

Share Document