Research on Strategies for Optimising Complex Systems Based on Monte Carlo Algorithms

In this paper, a mathematical model based on Monte Carlo algorithm is constructed for the optimisation problem of complex systems, focusing on the application of strategy optimisation in computer science. The model uses Pearson's coefficient to analyse the correlation between variables, including substitutability, complementarity, and the relationship between sales volume, price and cost, aiming to help users develop optimal decision-making strategies in the face of market volatility and uncertainty. By simulating the strategies under different scenarios, the model derives the optimal decisions under different conditions in each period, and compares and analyses the returns under different strategies. The results show that the optimised strategies perform well in terms of risk control, return stability and long-term benefits, providing an effective reference for strategy optimisation.