Importance The article investigates the problem of company’s procurement optimization, which consists of defining a set of goods to be ordered so as to maximally supply the demand of buyers under a limited budget. Objectives The aims are to develop an algorithm to solve the problem of procurement optimization by defining the smallest value of objective function, adjust the obtained values by using inverse computation, compare the obtained results with classical methods. Methods I employ classical methods for solving nonlinear programming problems, namely, the penalty method and the Lagrange multiplier technique. To solve the optimization problem, I use the inverse computation method. Results I developed an algorithm for solving the procurement optimization problem by means of inverse computation. In the algorithm, a solution obtained through unconstrained optimization is adjusted with regard to restrictions on available budget. The offered algorithm can be used in the decision support systems for procurement planning. Conclusions The presented algorithm is more straightforward for computer implementation as compared with classical methods. A solution to procurement optimization problem comes down to solving simultaneous equations. Computational experiments showed the same results for the three methods: inverse computation, penalty, and Lagrange multipliers.
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