Abstract: Against the backdrop of China’s“dual-carbon”goals，the optimization of natural gas pipeline operations has attracted keen academic interest as it can effectively cut costs，improve efficiency，and help achieve carbon reduction.Stochastic optimization algorithms show advantages over classical deterministic algorithms in dealing with large-scale pipeline networks and mixed-integer nonlinear programming（MINLP）problems.This paper investigates the optimization of natural gas pipeline operations based on stochastic optimization algorithms.Firstly，a mathematical model for natural gas pipeline operations is built.Secondly，stochastic optimization algorithms are employed to achieve optimal scheduling results.Four types of algorithms including genetic algorithms，particle swarm optimization，ant colony optimization，and simulated annealing are employed to analyze，compare，and generalize their applications in natural gas pipeline operations.Finally，the technical challenges and development trends of natural gas pipeline network operation optimization technology are discussed.