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The paper presents the results concerning computational burden analysis of dynamic programming and bottom-up algorithms when solving knapsack problems. It presents the efficiency of the algorithms information expressed both in calculation time, as well as mean number of iterations in knapsack problems up to 15,000 items and capacity of the knapsack equal to 10,000. The aim of the paper is to present the this knowledge what of practical use when solving optimization problems where estimate of execution time of the algorithm is important.

Computational Burden Analysis for Integer Knapsack Problems Solved with Dynamic Programming