Research on the decision-making method of coal order price and coal purchase quantity based on prediction

Abstract

The imbalance of coal supply and uncertainty of demand changes have brought great challenges to the stable supply of coal. In the actual trading process, there are problems such as variable demand and incomplete information on both, and the trading process lacks scientific and effective guidance. Therefore, game theory is introduced into the coal trading process, and a decision-making method based on predicted coal supply and demand order price and coal purchase quantity is proposed. Firstly, the prediction method is introduced, and the Long Short Term Memory (LSTM) and Autoregressive Integrated Moving Average Model (ARIMA) model are used to predict the coal purchase quantity and coal price of the supply and demand, which provides a basis for the formulation of the initial scheme of the bilateral game between supply and demand. Secondly, a bilateral game model of coal supply and demand based on prediction is established, and a bilateral order game-solving strategy of coal supply and demand based on a genetic algorithm is proposed. Finally, the proposed method was verified by setting up three different example scenarios for thermal coal trading, and the optimal coal price and coal purchase quantity under equilibrium are solved, and the results showed that the profit of supply and demand is increased by 4.65% and 2.97%, respectively, and the calculation time is reduced by 21.12%, which improves the speed of solving the game model, maximizes the benefits of both the coal supply and demand sides and provides a theoretical basis for the scientific and efficient order formation of coal mining enterprises.