An improved ant colony algorithm for MapReduce-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.