Solving Decision Making Problems in Production Processes Based on Bayesian Approach and Snake Optimization Algorithm

In this paper, we study the decision-making problem in the production process to maximize the net profit by using the unit net profit optimization model and the discrete snake optimization algorithm. Firstly, a sampling and testing scheme based on Bayesian method is proposed to design the prior distribution, update the posterior distribution and determine the termination conditions to output the minimum number of tests. Secondly, a two-layer optimization model of unit net profit is constructed to comprehensively consider the cost and profit of each link in production. Finally, the discrete snake optimization algorithm is used to solve the model, and the optimal solution is approximated through specific operation steps to obtain the best decision-making scheme and net profit, which provides a reference for production decision-making.