Optimization of Inventory in a Logistics System Using Nonlinear Programming Methods (In Russ.)

The article discusses key tasks and methods for optimizing and managing inventory in a logistics system to minimize the total cost of storing goods in a warehouse, as well as optimizing the cost of placing orders based on order volume relative to demand. The aim of the work is to develop a mathematical model for a nonlinear programming problem to minimize costs, taking into account the nonlinear functions of demand and storage costs, as well as inventory and or-der quantity constraints. The authors formulated a nonlinear inventory optimization problem as a nonlinear program-ming problem, for which a genetic algorithm was applied. Python programs have been developed for practical use. The developed toolkit makes it possible to find solutions for complex nonlinear inventory optimization problems, which enables the company to reduce overall operating costs, increase turnover, improve customer service, minimize excess inventory, optimize resources, and improve the company's financial performance.