Improvement of ant colony algorithm based on cloud models theory

Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

Volumn 37, Issue 1, 2005, Pages 115-119

  Duan, Hai Bin ^a   Wang, Dao Bo ^a   Yu, Xiu Fen ^b   Zhu, Jia Qiang ^c  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b CENTER FOR SPACE SCIENCE AND APPLIED RESEARCH   (China)

^c TSINGHUA UNIVERSITY   (China)

Author keywords

Ant colony algorithm; Cloud models theory; Pheromone; Qualitative association rule

Indexed keywords

COMPUTER SIMULATION; GLOBAL OPTIMIZATION; MATHEMATICAL MODELS; NUMERICAL ANALYSIS; OPTIMIZATION;

ANT COLONY ALGORITHM; CLOUD MODELS THEORY; PARALLELIZED BIONIC ALGORITHM; PHEROMONE; QUALITATIVE ASSOCIATION RULE;

GENETIC ALGORITHMS;

EID: 14744293801     PISSN: 03676234     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

1. ALBERTO C, MACRO D, VITTORIO M, et al. Distributed optimization by ant colonies[A]. Proceedings of European Conference on Artificial Life[C]. 1991. 134-142.
2. MACRO D, VITTORIO M, ALBERTO C. The ant system: optimization by a colony of cooperating agents[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1996, 26(1): 29-41.
3. MACRO D, MARIA G L. Ant colony system: a cooperative learning approach to the traveling salesman problem[J]. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 53-66.
4. BONABEAU E, JIABEN Y. Inspiration for optimization from social insect behaviour[J]. Nature, 2000, 406(6): 39-42.
5. STUTZLE T, HOOS H H. Max-min ant system[J]. Future Generation Computer Systems, 2000, 16(8): 889-891.