Optimization of the average monthly cost of an EOQ inventory model for deteriorating items in machine learning using PYTHON

In many stock disintegration issues of the real world, decay pace certain things might be influenced by other contiguous things. Depending on situation, influence weakened items can reduced eliminating them through examination. We specify a model that impacts average monthly cost, and non-linear programming Lagrangian method is solved specified model. The fuzzify inventory used to determine lowest cost employing trapezoidal fuzzy number, defuzzification process performed using graded mean integration representation method. To test model, we created CSV file, PYTHON (version 3.8.5), developed program predict economic order quantity total cost.