Title :
Underwater glider task allocation based on the ant colony algorithm
Author :
Shaoxuan Ren ; Yong Mei
Author_Institution :
Sch. of Mech. Eng., Shenyang Ligong Univ., Shenyang, China
Abstract :
The ant colony algorithm is an intelligence-optimized algorithm introduced by simulating ants searching for food by seeking the shortest route through pheromone. It is very useful in solving certain complicated optimization. This paper solves task allocation problem that an underwater glider deals with multiple tasks according to their situations, finished time and importance. The simulation results show that the ant colony algorithm is feasible and effective in solving tasks allocation.
Keywords :
autonomous underwater vehicles; optimisation; search problems; ant colony algorithm; ant food searching simulation; intelligence-optimized algorithm; pheromone; shortest route; underwater glider task allocation; Algorithm design and analysis; Biological cells; Genetic algorithms; Genetics; Heuristic algorithms; Resource management; Robots; ant colony algorithm; tasks allocation; underwater glider;
Conference_Titel :
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location :
Shenyang
DOI :
10.1109/ICNC.2013.6818044
