公开(公告)号：US20130275277A1

公开(公告)日：2013-10-17

申请号：US13673347

申请日：2012-11-09

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Kresimir MIHIC ,  Andrew VAKHUTINSKY ,  David VENGEROV

IPC: G06Q10/06

CPC classification number: G06Q10/06313 ,  G06Q10/04 ,  G06Q30/06

Abstract: A system for optimizing shelf space placement for a product receives decision variables and constraints, and executes a Randomized Search (“RS”) using the decision variables and constraints until an RS solution is below a pre-determined improvement threshold. The system then solves a Mixed-Integer Linear Program (“MILP”) problem using the decision variables and constraints, and using the RS solution as a starting point, to generate a MILP solution. The system repeats the RS executing and MILP solving as long as the MILP solution is not within a predetermined accuracy or does not exceed a predetermined time duration. The system then, based on the final MILP solution, outputs a shelf position and a number of facings for the product.

Abstract translation: 用于优化产品的货架空间布局的系统接收决策变量和约束，并且使用决策变量和约束来执行随机搜索（“RS”），直到RS解低于预定的改进阈值。 系统然后使用决策变量和约束解决混合整数线性规划（“MILP”）问题，并使用RS解决方案作为起点，以生成MILP解决方案。 只要MILP解决方案不在预定精度内或者不超过预定的持续时间，则该系统重复RS执行和MILP求解。 然后，系统基于最终的MILP解决方案，输出产品的货架位置和多个面板。

公开(公告)号：US20250131342A1

公开(公告)日：2025-04-24

申请号：US18610745

申请日：2024-03-20

Applicant: Oracle International Corporation

Inventor： Andrew VAKHUTINSKY ,  Zijie ZHOU

IPC: G06Q10/02 ,  G06N20/00 ,  G06Q50/12

Abstract: Embodiments optimize hotel room reservations for a hotel. For a first day of a plurality of future days, embodiments automatically determine, based on an objective function, an overbooking limit for each category of hotel rooms for the hotel, where the hotel includes a plurality of different room categories. Embodiments receive a first reservation request for the first day for a first category room. When the determined overbooking limit for the first category room has not been reached, embodiments accept the first reservation request. When the accepted first reservation request is being checked in to the hotel on the first day, embodiments automatically determine, based on the objective function, to reject the first reservation request, accept the first reservation request, or upgrade the first reservation request to a higher category room.

公开(公告)号：US20230376861A1

公开(公告)日：2023-11-23

申请号：US17746282

申请日：2022-05-17

Applicant: Oracle International Corporation

Inventor： Andrew VAKHUTINSKY ,  Jorge Luis Rivero PEREZ ,  Kirby BOSCH ,  Jason G BRYANT ,  Natalia KOSILOVA

IPC: G06Q10/02 ,  G06Q30/06 ,  G06Q50/12

CPC classification number: G06Q10/02 ,  G06Q30/0631 ,  G06Q50/12

Abstract: Embodiments upsell a hotel room selection by providing a first plurality of hotel room choices, each first plurality of hotel room choices comprising a first type of hotel room and a corresponding first price. Embodiments receive a first selection of one of the first plurality of hotel room choices. In response to the first selection, embodiments provide a second plurality of hotel room choices, the second plurality of hotel room choices comprising a subset of the first types of hotel room choices and a corresponding optimized price that is different from the respective corresponding first price.

公开(公告)号：US20220358436A1

公开(公告)日：2022-11-10

申请号：US17231252

申请日：2021-04-15

Applicant: Oracle International Corporation

Inventor： Andrew VAKHUTINSKY

IPC: G06Q10/06 ,  G06Q30/02

Abstract: Embodiments optimize inventory allocation of a retail item, where the retail item is allocated from a plurality of different fulfillment centers to a plurality of different customer groups. Embodiments receive historical sales data for the retail item and estimate demand model parameters. Embodiments generate a network including first nodes corresponding to the fulfillment centers, second nodes corresponding to the customer groups, and third nodes between the first nodes and the second nodes, each of the third nodes corresponding to one of the second nodes. Embodiments generate an initial feasible inventory allocation from the first nodes to the second nodes and solves a minimum cost flow problem for the network to generate an optimal inventory allocation.

公开(公告)号：US20200380452A1

公开(公告)日：2020-12-03

申请号：US16426360

申请日：2019-05-30

Applicant: Oracle International Corporation

Inventor： Andrew VAKHUTINSKY ,  Kiran V. PANCHAMGAM ,  Su-Ming WU

IPC: G06Q10/08 ,  G06Q30/02 ,  G06Q10/04

Abstract: Embodiments optimize the inventory allocation of a retail item that is provided from a plurality of warehouses to a plurality of price zones, each of the warehouses adapted to allocate inventory of the retail item to at least two of the price zones via links. Embodiments generate an initial inventory allocation for each warehouse to price zone link to generate a plurality of warehouse to price zone allocations. For each of the warehouse to price zone allocations, embodiments determine a marginal profit as a function of inventory allocated. Embodiments construct a bi-partite graph corresponding to each warehouse to price zone allocation, each bi-partite graph having a link weight equal to the marginal profit. Embodiments determine when there is a positive weight path between any two price zones and then reallocate the initial inventory allocation and repeat the functionality.

公开(公告)号：US20200342475A1

公开(公告)日：2020-10-29

申请号：US16380185

申请日：2019-04-10

Applicant: Oracle International Corporation

Inventor： Su-Ming WU ,  Andrew VAKHUTINSKY ,  Setareh Borjian BOROUJENI ,  Santosh Bai REDDY ,  Kiran V. PANCHAMGAM ,  Sajith VIJAYAN ,  Mengzhenyu ZHANG

IPC: G06Q30/02 ,  G06Q10/06 ,  G06F17/17

Abstract: Embodiments determine a price schedule for an item by, for each item, receiving a set of prices for the item, an inventory quantity for the item, a per-segment demand model for the item, and an objective function that is a function of the per-segment demand model and maximizes revenue based at least on a probability of a return of the item and a cost of the return. Embodiments allocate the inventory quantity among a plurality of customer segments based at least on a predicted contribution of each customer segment to the objective function. Embodiments determine a markdown portion of the price schedule for the item that maximizes the objective function, where the markdown portion assigns a series of prices selected from the set of prices for respective time periods during a clearance season for the item.