In view of the scheduling optimization problem of the combined cooling heating and power microgrid system with multi-renewable energy, a multi-objective scheduling optimization model is established, which includes minimum operation cost and minimum carbon dioxide emission. The Pareto optimal solution set is obtained through heuristic scheduling rules and the improved multi-objective cross entropy(MOCE) algorithm. The multi-objective optimization is defined as a small probability event based on the important sampling theory, and the sample section generation strategy and parameter updating mechanism are introduced to improve the convergence speed and accuracy of the algorithm. Simulation results show that the proposed multi-objective model and algorithm can ensure the better economic and environmental benefits of the system, and also meet the diversified optimization requirements of users.