首页|'Optimization Of Hyperparameters For Training A Surge Pricing Model For An Onlin e Concierge System' in Patent Application Approval Process (USPTO 20240289828)
'Optimization Of Hyperparameters For Training A Surge Pricing Model For An Onlin e Concierge System' in Patent Application Approval Process (USPTO 20240289828)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A patent application by the inventors Ashby, Brendan Evans (San Francisco, CA, US); Bor, Bryan Daniel (Pittsburg, CA, US); Miziolek, Konrad Gustav (San Francisco, CA, US); Singh, Shivee (Sunnyvale, CA, US); Srinivasan, Nikita (San Francisco, CA, US); Sturm, Nicholas (Denver, CO , US); Xu, Xiaofan (Fremont, CA, US); Zhang, Wenhui (Redwood City, CA, US), file d on February 23, 2023, was made available online on August 29, 2024, according to news reporting originating from Washington, D.C., by NewsRx correspondents. This patent application has not been assigned to a company or institution. The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “In an online concierge system, customers may se lect items for ordering, procurement and delivery from physical retailers or ot her warehouses. The online concierge system assigns orders to available shoppers that fulfill the orders for a fee. In such a system, the supply and demand for shoppers can vary significantly over different times of day, different days of t he week, during holidays, or based on various other factors. To reduce dispariti es in supply and demand, the online concierge system may employ a surge pricing model in which the wages offered to shoppers dynamically adapt under various con ditions. However, there is a tradeoff between the additional costs associated wi th surge pricing versus the benefit of encouraging more shoppers to fulfill orde rs during a given time period. Effective deployment of an optimal surge pricing model thus remains a challenge.”
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