A Parallel Pre-schedule Max-Min Ant System.

The parameter sensitivity of MMAS algorithm is analyzed in this paper. And then, we propose a multi-ant colony parallel optimization algorithm based on dynamic parameter adaptation strategy, aiming at the performance lack of traditional ACO algorithm. This algorithm makes use of cloud computing parallelism to design and analyze the MMAS system. The convergence solution comparison results show that this method has certain advantages.