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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2003, Vol. 4 Issue (1): 40-46    DOI: 10.1631/jzus.2003.0040
Information & Computer Technology     
An adaptive ant colony system algorithm for continuous-space optimization problems
Li Yan-jun, Wu Tie-jun
Institute of Intelligent Systems and Decision Making, Zhejiang University, Hangzhou 310027, China
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Abstract  Ant colony algorithms comprise a novel category of evolutionary computation methods for optimization problems, especially for sequencing-type combinatorial optimization problems. An adaptive ant colony algorithm is proposed in this paper to tackle continuous-space optimization problems, using a new objective-function-based heuristic pheromone assignment approach for pheromone update to filtrate solution candidates. Global optimal solutions can be reached more rapidly by self-adjusting the path searching behaviors of the ants according to objective values. The performance of the proposed algorithm is compared with a basic ant colony algorithm and a Square Quadratic Programming approach in solving two benchmark problems with multiple extremes. The results indicated that the efficiency and reliability of the proposed algorithm were greatly improved.

Key words： Ant colony algorithm      Continuous-space optimization      Pheromone update strategy     
Received: 29 December 2001     
CLC:  TP202  
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Li Yan-jun, Wu Tie-jun. An adaptive ant colony system algorithm for continuous-space optimization problems. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2003, 4(1): 40-46.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2003.0040     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2003/V4/I1/40

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