Ant colony algorithm is an Italian scholar Dorigo et al. [1, 2], in the early 1990s, simulated the natural world A population based inspiration for the behavior of the collective size of the ants Bionic evolution system. Ant colony algorithm consists of two basic stages: adaptive order Segment and collaboration phase. In the adaptive phase, the candidate solutions are based on accumulated information Constantly adjust your structure. During the collaboration phase, the candidate solution passes information Communication, in order to produce better solutions, is similar to learning automata Learning mechanism. Ant colony algorithm is successfully used to solve the famous brigade Business problem (t raveling salesman problem, TSP), this algorithm is adopted The distributed positive feedback parallel computing mechanism is used to facilitate the junction with other methods Combined with strong robustness [325]. Ant colony algorithm has been established for more than 10 years, whether in algorithm theory or computation There have been many breakthroughs in the application of law.

Packet : 29782205ant.rar filelist
ant\ant.dsp
ant\ant.dsw
ant\Text1.txt
ant\Debug
ant
ant\ant.ncb
ant\ant.opt

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