Title :
Adaptive multi-objective ant colony algorithm based on cloud model
Author :
Xu Li;Zhengyan Liu;Shibing Wang
Author_Institution :
School of computer and information engineering, Fuyang Teachers College, Anhui Province, China
Abstract :
In this paper, the cloud model theory and ant colony algorithm are combined to explore and build cloud model adaptive mechanism in multi-target environment, and an adaptive multi-objective ant colony algorithm based on cloud model is proposed. Through the evaluation of pheromone distribution, the parameters of the cloud model are adjusted adaptively, and then the range of optimum dominated solutions is determined dynamically. Therefore, the algorithm can achieve a balance between development and exploration, and improve the efficiency of the Pareto frontier exploration. Simulation results show that the proposed algorithm can obtain high-quality Pareto optimal solutions, the effect is significant.
Keywords :
"Adaptation models","Heuristic algorithms","Entropy","Computational modeling","Algorithm design and analysis","Pareto optimization"
Conference_Titel :
Information and Automation, 2015 IEEE International Conference on
DOI :
10.1109/ICInfA.2015.7279734