DocumentCode
2838102
Title
A Quantum-Inspired Ant Colony Optimization for robot coalition formation
Author
Yu, Zhang ; Shuhua, Liu ; Shuai, Fu ; Di, Wu
Author_Institution
Sch. of Comput. Sci., Northeast Normal Univ., Changchun, China
fYear
2009
fDate
17-19 June 2009
Firstpage
626
Lastpage
631
Abstract
A quantum-inspired ant colony optimization (QACO), based on the concept and principles of quantum computing is proposed in this paper to improve the ability to search and optimization of ant colony optimization (ACO). Each ant is a quantum individual and instead of Q-bit code, we use the probability of choosing robots, and QACO is successfully applied to solve robot coalition formation. The simulated results show that QACO has the better diversity of population and ability to search and optimization, and performs well, even with a small population, without premature convergence as compared to ACO.
Keywords
combinatorial mathematics; multi-robot systems; optimisation; probability; quantum computing; search problems; Q-bit code; QACO; combinatorial optimization problem; multirobot system; premature convergence; probability; quantum computing; quantum-inspired ant colony optimization; robot coalition formation; search problem; Ant colony optimization; Cameras; Computational modeling; Computer science; Convergence; Mobile robots; Quantum computing; Quantum mechanics; Robot sensing systems; Robot vision systems; Large-scale robots; QACO; Robot Coalition Formation; Task Allocation; task allocation;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location
Guilin
Print_ISBN
978-1-4244-2722-2
Electronic_ISBN
978-1-4244-2723-9
Type
conf
DOI
10.1109/CCDC.2009.5194884
Filename
5194884
Link To Document