An improved Ant Colony algorithm for Map Reduce based Fleet Assignment Problem
To solve the large-scale fleet assignment in cloud computing,an improved ant colony optimization algorithm in MapReduce framework is proposed.Based on the traditional ant colony algorithm,pheromone selection and update mechanisms are improved,and two algorithms involving different MapReduce processing modes are further proposed.Numerical results show that the proposed algorithm not only improves the ability to solve the large-scale problem,but also improves the quality of optimal solution and algorithm convergence.Moreover,the second algorithm is more efficient on calculation time reducing than the first algorithm.
cloud computing MapReduce frame fleet assignment problem ant colony optimization algorithm
Zheng Yang Ying Yu Kang Zhang Hongjie Kuang Weijie Wang
Institute of Electromechanical Engineering and Automation,Shanghai University Shanghai,China
国际会议
重庆
英文
104-108
2017-03-25(万方平台首次上网日期,不代表论文的发表时间)