This paper introduces a novel numerical stochastic optimization algorithm inspired from the behaviors of cloud in the natural world, which is designated as atmosphere clouds model optimization (ACMO) algorithm. It is tried to simulate the generation behavior, move behavior and spread behavior of cloud in a simple way. The ACMO algorithm has been tested on a set of benchmark functions in comparison with two other evolutionary-based algorithms: particle swarm optimization (PSO) algorithm and genetic algorithm (GA). The results demonstrate that the proposed algorithm has certain advantages in solving multimodal functions, while the PSO algorithm has a better result in terms of convergence accuracy. In conclusion, the ACMO algorithm is an effective method in solving optimization problems.
PID2018 Benchmark Challenge: Multi-Objective Stochastic Optimization Algorithm