Author:
Odili J B.,Noraziah A.,Mohd Sidek Roslina
Abstract
Abstract
This paper presents research findings on the application of swarm intelligence techniques in computational intelligence to solve the travelling salesman’s problem. The travelling salesman’s problem finds real-life application in post office mail delivery, school bus routing, delivery of food to home-bound people etc. After a number of experimental procedures, the study concludes that all the comparative algorithms are very efficient in providing solutions to the benchmark travelling salesman’s problems considered, though the Discrete Cuckoo Search and the African Buffalo Optimization have a slight edge in performance over the other comparative algorithms. In all, the study agrees with earlier studies in reaching the conclusion that swarm-based optimization techniques are not only effective but also are very efficient in providing solutions to the travelling salesman’s problems.
Reference31 articles.
1. Application of Ant Colony Optimization to Solving the Traveling Salesman’s Problem;Odili,2013
2. Ant-Q: A reinforcement learning approach to the traveling salesman problem;Dorigo
3. The Effect Of The Asymmetry Of Road Transportation Networks On The Traveling Salesman Problem;Rodríguez;Computers & Operations Research,2012
4. Theory of Scheduling;Conway,2012
5. Effective Coverage Control for Mobile Sensor Networks with Guaranteed Collision Avoidance;Hussein;IEEE Transactions on Control Systems Technology,2007
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献