However, most of them assume the unrealistic assumption that unit profits of items remain unchanged over time.
It consists of discovering sets of items generating a high profit in a transactional database by considering both purchase quantities and unit profits of items.
One agent packs items into his knapsack to maximize the total profit, while another agent can only pack items into his knapsack as well but he cares about the total profits of items packed into two knapsacks.
However, in this case the profit of such items may vary.
Furthermore, we propose two profit-based scheduling algorithms, PVC and SSA, for single- and multi-channel scheduling, respectively, both of which utilize our new concept "profit" of pending items and "opportunity cost" of pending requests.
But in real-life, the profit of an item or itemset varies as a function of cost prices, sales prices and sale strategies.
The profit of an item corresponds to the negative of the PSNR distortion, −d(f ij ″, f ij ), and the weight of an item to the frame rate, r( f ij ).
Indeed, using scaled profits p ˜ j ≔ ⌊ p j n / (ε p max ) ⌋, where p max is the largest profit of an item, one obtains an FPTAS for (RKP) with running time O (Γ n 3 / ε ) (neglecting the details of retrieving the corresponding solution set, cf. Section 3).
High-utility itemset mining (HUIM) is an extension of frequent-itemset mining (FIM) but considers the unit profit and quantity of items to discover the set of high-utility itemsets (HUIs).
Though UBC is for profit, a third of items purchased are donated to The Salvation Army, Lions Club Sight First Program, medical mission teams and several locally-run Scottsboro charities.
