Title :
Research and realization on the ant colony optimization algorithm
Author :
Xuzhi Wang ; Yuanzheng Liu ; Yangyang Jia
Author_Institution :
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
Abstract :
This is where the abstract should be placed. It should consist of one paragraph and a concise summary of the material discussed in the article below. It is preferable not to use footnotes in the abstract or the title. The acknowledgement for funding organisations etc. is placed in a separate section at the end of the text. We wish you success with the preparation of your manuscript. The ant colony algorithm (ACA ) is a simulated evolutionary algorithm , which is inspired by real ants foraging in natural world. In this paper, it has effectively solved the problem of precocity and halting of the ant colony algorithm, taking use of the global and rapidity of the PSO. Meanwhile, it can also judge the standard of the route by use of the eliminating- cross. Through classic experiments about Traveling Salesman Problem, the optimization algorithm has the better astringency, robustness and efficiency.
Keywords :
ant colony optimisation; evolutionary computation; travelling salesman problems; ACA; ant colony algorithm; ant colony optimization algorithm; funding organisations; simulated evolutionary algorithm; traveling salesman problem; Ant Colony Algorithm (ACA); Eliminating-cross; Particle Swarm Optimization (PSO); Traveling Salesman Problem (TSP);
Conference_Titel :
Wireless Mobile and Computing (CCWMC 2011), IET International Communication Conference on
Conference_Location :
Shanghai
DOI :
10.1049/cp.2011.0894