Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution

In this paper, we study a distribution-free multi-period newsvendor problem with advance purchase discount (APD). addition to the regular-order placed at beginning of each period, decision-maker (DM) can also commit an advance-order from upstream supplier and receive discounts. The goal DM is maximize total profits, in problem, only has access past demand data. To solve apply online method based on theory prediction learning expert advice propose explicit ordering solution by using fixed-stock policy as advice. With properties gain function, derive theoretical result that guarantees, for any given quantity, newsvendor’s cumulative gains achieved proposed converge those best hindsight sufficient large horizon. addition, extend discrete case obtain corresponding strategy performance guarantee. Finally, numerical studies illustrate effectiveness solution, profits are comparable Sensitivity analysis shows robustness solution.