NDLI: An improved ant colony algorithm and simulation

Content Provider	IEEE Xplore Digital Library
Author	Li Xin Yu Datai Qin Jin
Copyright Year	2009
Description	Author affiliation: Information Engineering School, University of Science and Technology in Beijing, 100083, China (Li Xin; Yu Datai; Qin Jin)
Abstract	We demonstrate a novel Ant Colony System with dynamically varied parameters and a penalty-reward function, which is based on the Basic Ant System (BAS) algorithm, also presented is its application to solving complex TSP problem. Our new algorithm has two important features, the first: a perturbation factor formulated by inverse exponent penalty-reward function is developed; the second: a corresponding transition strategy with random selection is designed. Numerical simulation demonstrates that our new algorithm has much higher convergence speed and stability than BAS algorithm, and brings along good effects of reducing CPU time, and preventing search from being in stagnation behavior.
Starting Page	2838
Ending Page	2841
File Size	105193
Page Count	4
File Format	PDF
ISBN	9781424427222
DOI	10.1109/CCDC.2009.5191799
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computational modeling Biological system modeling Roads Educational institutions Pheromone Application software Computer science TSP Information science Penalty-Reward Function Ant Colony Cities and towns Numerical simulation
Content Type	Text
Resource Type	Article

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