Simulation of Enterprise Management Combination Optimization Model Based on Bp Neural Network Algorithm

This article introduces the Back Propagation Neural Network (BPNN) algorithm to address issues such as unreasonable resource allocation, imbalanced investment portfolios, and low decision-making efficiency in enterprises. The aim is to construct an effective model for optimizing enterprise management portfolios. This model can accurately predict the effects of different combination schemes through data training, and dynamically adjust enterprise management strategies to achieve optimized configuration. Firstly, by collecting and organizing multidimensional historical data such as financial statements, operational data, and market environment, key factors that affect the efficiency of enterprise management, such as fund liquidity, market volatility, and human resource allocation, are extracted. Then, based on the extracted key influencing factors, a three-layer BPNN model is constructed. The input layer is used to receive resource allocation data, the middle layer performs weight optimization and nonlinear mapping, the output layer predicts the optimal management combination, and dynamically adjusts resource allocation and combination optimization through multiple rounds of simulation. Finally, based on the simulation results, the weights and parameters are repeatedly adjusted, and the optimal management combination scheme such as investment ratio optimization, cost control strategy, and human resource allocation optimization is obtained through multiple iterations of optimization. The simulation results of the model show that the enterprise management portfolio optimization model based on BPNN algorithm can effectively improve resource utilization, reduce operating costs, and significantly improve decision-making efficiency. Compared to traditional methods, simulation results show that the optimized management portfolio model significantly reduces enterprise risk by 8 %, while increasing investment return by 12 %. The enterprise management portfolio optimization model based on BPNN algorithm can effectively solve the core problems of resource allocation and decision optimization in enterprises, and has strong practical application value. By further optimizing the model parameters, it is expected to be widely applied in more enterprise management scenarios.