Title :
Test Paper Problem Solved by Binary Ant Colony Algorithm
Author :
Meiying Cheng ; Xiong, Weiqing
Author_Institution :
Dept. of Comput. Sci. & Eng., Ningbo Univ., Ningbo
Abstract :
Through analyzing the mathematical model and objective function of the composing test paper, this article abstracts that the composing test paper model is really a multi-objective linear programming model, and the binary ant colony algorithm is introduced to solve the problem. Owning to the adoption of the binary coding, each ant chooses the subject or not only need to according to the strength of the pheromone on every edge, and the requirement for the behavior of every single ant is lower, so the corresponding memory is relatively less. Experimental results demonstrate that the algorithm can solve the test paper problem quickly and effectively, and also has practical value.
Keywords :
education; evolutionary computation; linear programming; binary ant colony algorithm; binary coding; mathematical model; multi-objective linear programming model; objective function; Abstracts; Algorithm design and analysis; Ant colony optimization; Computer science; Convergence; Genetic algorithms; Heuristic algorithms; Linear programming; Mathematical model; System testing;
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
DOI :
10.1109/ICICIC.2008.536