公开(公告)号：US20160210640A1

公开(公告)日：2016-07-21

申请号：US14600099

申请日：2015-01-20

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Su-Ming WU ,  Saraswati YAGNAVAJHALA

IPC: G06Q30/02 ,  G06Q10/08

CPC classification number: G06Q30/0202 ,  G06Q10/087

Abstract: Systems, methods, and other embodiments associated with incrementally swapping items in an assortment are described. In one embodiment, a computing system includes demand logic configured to read data from an electronic data structure that defines an assortment. The assortment defines a subset of items from a product category. The demand logic is configured to generate forecasted changes to an associated metric value by generating demand transference values for (i) individually removing each item presently in the assortment and (ii) individually adding each item of a set of available items of the product category. The computing system includes assortment logic configured to transform the electronic data structure that defines the assortment according to the forecasted changes by incrementally swapping items in the assortment for new items in the available set of items until the forecasted changes between items in the assortment and new items in the set of available items satisfy a predefined condition.

Abstract translation: 描述了与各种增量交换项目相关联的系统，方法和其他实施例。 在一个实施例中，计算系统包括被配置为从定义分类的电子数据结构读取数据的需求逻辑。 分类定义了产品类别中的一个子集。 需求逻辑被配置为通过生成需求转移值来产生对相关度量值的预测变化，所述需求转移值用于（i）单独地移除目前在分类中的每个项目，以及（ii）单独地添加产品类别的一组可用项目中的每个项目。 该计算系统包括分类逻辑，其被配置为根据预测的变化，通过递增交换可用项目集中的新项目的分类中的项目来变换定义分类的电子数据结构，直到分类中的项目和新项目之间的预测变化 在可用项目集合中满足预定义条件。

公开(公告)号：US20210117873A1

公开(公告)日：2021-04-22

申请号：US16736284

申请日：2020-01-07

Applicant: Oracle International Corporation

Inventor： Andrew VAKHUTINSKY ,  Setareh Borjian BOROUJENI ,  Saraswati YAGNAVAJHALA ,  Jorge Luis Rivero PEREZ ,  Dhruv AGARWAL ,  Akash CHATTERJEE

IPC: G06Q10/02 ,  G06Q10/04 ,  G06Q50/12 ,  G06Q10/06

Abstract: Embodiments provide optimized room assignments for a hotel in response to receiving a plurality of hard constraints and soft constraints and receiving reservation preferences and room features. The optimization includes determining a guest satisfaction assignment cost based on the reservation preferences and room features, determining an operational efficiency assignment cost, generating a weighted cost matrix based on the guest satisfaction assignment cost and the operational efficiency assignment cost, and generating preliminary room assignments based on the weighted cost matrix. When the preliminary room assignments are feasible, the preliminary room assignments are the optimized room assignments comprising a feasible selection of elements of the matrix. When the preliminary room assignments are infeasible, embodiments relax one or more constraints and repeat the performing optimization until the preliminary room assignments are feasible.

公开(公告)号：US20240394623A1

公开(公告)日：2024-11-28

申请号：US18321831

申请日：2023-05-23

Applicant: Oracle International Corporation

Inventor： Recep Yusuf BEKCI ,  Andrew VAKHUTINSKY ,  Saraswati YAGNAVAJHALA

IPC: G06Q10/0631 ,  G06Q10/04

Abstract: Embodiments optimize inventory assortment and allocation of a group of products, where the group of products are allocated from a plurality of different warehouses to a plurality of different retail stores. Embodiments receive historical sales data for the group of products and estimate demand model parameters of a demand model that models a demand of the group of products. Embodiments solve an optimization problem for the inventory assortment and allocation of the group of products, the optimization including a plurality of decision variables, an objective function, and a corresponding Lagrangian relaxation. The solving to generate an optimized solution includes determining a gradient of the objective function with respect to the decision variables, updating the decision variables based on a direction of the gradient and updating dual lambda variables of the Lagrangian relaxation.

公开(公告)号：US20210117998A1

公开(公告)日：2021-04-22

申请号：US16784634

申请日：2020-02-07

Applicant: Oracle International Corporation

Inventor： Sanghoon CHO ,  Andrew VAKHUTINSKY ,  Saraswati YAGNAVAJHALA

IPC: G06Q30/02 ,  G06Q50/12 ,  G06K9/62 ,  G06F17/18 ,  G06N5/00 ,  G06N20/00

Abstract: Embodiments model demand and pricing for hotel rooms. Embodiments receive historical data regarding a plurality of previous guests, the historical data including a plurality of attributes including guest attributes, travel attributes and external factors attributes. Embodiments generate a plurality of distinct clusters based the plurality of attributes using machine learning soft clustering and segment each of the previous guests into one or more of the distinct clusters. Embodiments build a model for each of the distinct clusters, the model predicting a probability of a guest selecting a certain room category and including a plurality of variables corresponding to the attributes. Embodiments eliminate insignificant variables of the models and estimate model parameters of the models, the model parameters including coefficients corresponding to the variables. Embodiments determine optimal pricing of the hotel rooms using the model parameters and a personalized pricing algorithm.