Research on Optimal Decision-Making of Enterprise Production Based on 0-1 Integer Programming and Bayesian Algorithm

This paper focuses on the problem of how an enterprise can maximize profits when purchasing spare parts and assembling them into finished products. First use simple random sampling, the introduction of the Deimoffer-Laplace central limit theorem, according to the hypothesis test in the test, the relationship between the critical value and the sample size, and then set the acceptable error range, under which the error range, respectively, designed in the confidence of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 5 \%}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 0 \%}$</tex> under the most in line with the enterprise standards of the sampling and testing program. Considering that the parts and finished products testing disassembled or not will affect its testing cost, which in turn affects the total cost of the enterprise, in order to maximize the profit, the optimization model is established by using 0 – 1 integer programming. Since the total cost of the enterprise is affected by the parts purchase cost, inspection cost, dismantling cost and exchange loss, and the total income of the enterprise is affected by the income of qualified products, dismantling income, and the income of the remaining parts, the decision variables and objective function of the optimization model are determined, the optimization model is established, and finally the optimal decision-making scheme and the maximum profit are obtained through the violent enumeration method. Considering the absence of actual samples and defective products, Bayesian method is used to estimate the defective rate, and then simple random sampling is used to derive the prior distribution, and simulation generates pseudodata, so that the posterior distribution can be calculated, and then the expectation of the posterior distribution can be the defective rate, and finally the results are examined and analyzed, which proves the correctness and reasonableness of the results.